Fix substation coordinate handling for cable crossing detection

- 重新启用run.io_bound()调用，使用后台线程执行PowerShell脚本
- 为所有文件保存操作添加按钮防重复点击功能
- 新增win32_helper模块，提供Win32 API和COM接口的文件对话框
- 简化导出最佳方案DXF的代码结构
- 改进异步操作和错误处理机制

.vscode/launch.json

@@ -0,0 +1,16 @@
+{
+  // Use IntelliSense to learn about possible attributes.
+  // Hover to view descriptions of existing attributes.
+  // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Python Debugger: Current File with Arguments",
+      "type": "debugpy",
+      "request": "launch",
+      "program": "main.py",
+      "console": "integratedTerminal",
+      "args": "--excel abc.xlsx"
+    },
+  ]
+}

IFLOW.md

@@ -0,0 +1,240 @@
+# 海上风电场集电线路设计优化系统 - 项目上下文
+
+## 项目概述
+
+这是一个用于设计和优化海上风电场集电系统拓扑的综合工具，专为海上能源业务开发部电气专业设计。该系统通过多种先进的拓扑优化算法（MST、旋转扫描法、Esau-Williams等），根据风机坐标、功率以及海缆规格，自动生成投资成本最低、损耗最优的设计方案。
+
+### 核心功能
+- 🖥️ **图形化界面**：基于 NiceGUI 的现代化桌面应用，支持原生窗口模式
+- 🌊 **多种布局生成**：支持规则网格和随机分布布局的模拟数据生成
+- 🔌 **多算法优化**：
+  - MST (Minimum Spanning Tree)：无容量约束基准方案
+  - Capacitated Sweep (Base)：基础扇区扫描分组
+  - Rotational Sweep：全局最优起始角度旋转扫描优化
+  - Esau-Williams：经典启发式算法，在距离与容量间寻找最优平衡
+- ⚙️ **灵活参数配置**：通过 Excel 自定义系统电压、功率因数、电价及电缆规格
+- 📊 **智能方案对比**：自动运行三大场景（标准方案、含可选电缆方案、限制最大截面方案）
+- 📁 **多格式导出**：CAD图纸(.dxf)、Excel报告、压缩包
+
+### 技术栈
+- **语言**：Python 3.12+
+- **GUI框架**：NiceGUI 3.4.1 + PyWebview 6.1
+- **核心库**：
+  - numpy 2.4.0：数值计算
+  - pandas 2.3.3：数据处理
+  - matplotlib 3.10.8：可视化
+  - scikit-learn 1.8.0：聚类算法
+  - networkx 3.6.1：图算法
+  - ezdxf 1.4.3：CAD导出
+  - scipy 1.16.3：科学计算
+
+## 项目结构
+
+```
+D:\code\windfarm\
+├── main.py                 # 核心算法和业务逻辑（1388行）
+├── gui.py                  # NiceGUI图形界面（1067行）
+├── esau_williams.py        # Esau-Williams算法实现（242行）
+├── generate_template.py    # Excel模板生成器
+├── make_version.py         # 版本号自动生成脚本
+├── pyproject.toml          # 项目依赖配置
+├── Makefile                # 构建脚本
+├── 使用说明/               # 中文操作手册和截图
+├── build/                  # 构建输出目录
+└── dist/                   # 打包输出目录
+```
+
+## 构建和运行
+
+### 环境配置
+项目使用 `uv` 作为包管理器，也支持 `pip`：
+
+```bash
+# 使用 uv（推荐）
+uv sync
+
+# 或使用 pip
+pip install -r requirements.txt  # 如果有requirements.txt
+# 或手动安装依赖
+pip install numpy pandas matplotlib scikit-learn scipy networkx ezdxf nicegui openpyxl pywebview
+```
+
+### 运行方式
+
+#### 1. 图形化界面（推荐）
+```bash
+python gui.py
+```
+启动后，程序将弹出独立窗口，提供完整的交互式界面。
+
+#### 2. 命令行模式
+```bash
+python main.py --excel your_data.xlsx
+```
+
+### 构建可执行文件
+
+使用 Makefile 进行构建：
+
+```bash
+# 构建exe文件（自动生成版本号）
+make build
+
+# 重新构建（先清理再构建）
+make rebuild
+
+# 清理构建文件
+make clean
+
+# 查看帮助
+make help
+```
+
+构建过程：
+1. 运行 `make_version.py` 生成版本号
+2. 使用 `nicegui-pack` 打包为单文件exe
+3. 重命名输出文件包含版本号
+
+构建输出位于 `dist/` 目录，文件名格式：`海上风电场集电线路设计优化系统_{VERSION}.exe`
+
+## 输入数据规范
+
+### Excel文件格式
+输入Excel文件应包含以下三个Sheet：
+
+#### 1. Coordinates（坐标数据）- 必需
+| Type | ID | X | Y | Power | PlatformHeight |
+|------|----|---|---|-------|----------------|
+| Substation | Sub1 | 4000 | -800 | 0 | 0 |
+| Turbine | 1 | 0 | 0 | 8.0 | 25 |
+
+- **Type**: `Substation` 或 `Turbine`
+- **X/Y**: 投影坐标（米），建议使用高斯投影坐标
+- **Power**: 功率（MW），升压站填0
+- **PlatformHeight**: 塔筒/平台高度（米）
+
+#### 2. Cables（电缆规格）- 必需
+| CrossSection | Capacity | Resistance | Cost | Optional |
+|--------------|----------|------------|------|----------|
+| 35 | 150 | 0.524 | 80 | |
+| 400 | 580 | 0.0470 | 600 | Y |
+
+- **CrossSection**: 导体截面（mm²）
+- **Capacity**: 额定载流量（A），需考虑降容系数
+- **Resistance**: 交流电阻（Ω/km）
+- **Cost**: 综合单价（元/m）
+- **Optional**: 可选标记（Y表示可选大截面电缆）
+
+**重要规则**：
+- 电缆必须按截面从小到大排列
+- `Optional` 为 'Y' 的电缆最多只能有一条
+- 若存在可选电缆，它必须是列表中截面最大的一条
+
+#### 3. Parameters（系统参数）- 必需
+| Parameter | Value |
+|-----------|-------|
+| Voltage (kV) / 电压 (kV) | 66 |
+| Power Factor / 功率因数 | 0.95 |
+| Electricity Price (元/kWh) / 电价 (元/kWh) | 0.4 |
+
+## 核心算法说明
+
+### 1. MST（最小生成树）
+- **原理**：基于 Kruskal 或 Prim 算法，寻找连接所有风机且总路径长度最短的树状结构
+- **特点**：不考虑电缆载流量限制，仅作为理论距离基准参考
+- **适用场景**：小规模风电场的理论分析
+
+### 2. Capacitated Sweep（基础扇区扫描）
+- **原理**：以升压站为中心，将平面划分为扇区，按顺时针扫描风机
+- **特点**：计算速度快，拓扑结构简单清晰
+- **局限**：对起始扫描角度敏感，可能产生"长尾巴"连线
+
+### 3. Rotational Sweep（旋转扫描优化）
+- **原理**：尝试 0° 到 360° 之间的所有起始扫描角度
+- **优势**：比基础扫描法节省 3%~8% 的线缆成本
+- **适用场景**：最接近人工精细化排布的自动化算法
+
+### 4. Esau-Williams 启发式算法
+- **原理**：约束最小生成树（CMST）算法，迭代计算互联操作的成本节省
+- **优势**：能发现树状、多分叉等复杂但更经济的拓扑结构
+- **适用场景**：风机分布不规则、离岸距离较远或电缆造价极高的情况
+
+## 方案场景说明
+
+系统自动运行三种场景：
+
+1. **Scenario 1 (Standard)**：仅使用非可选（标准）电缆进行优化
+2. **Scenario 2 (With Optional)**：包含标记为 'Y' 的大型电缆，适用于尝试增加单回路容量
+3. **Scenario 3 (No Max)**：排除最大截面电缆，测试电缆供应受限时的最优拓扑
+
+## 输出文件说明
+
+- **Excel报告**：`[文件名]_result.xlsx` - 包含所有方案总览及详细连接清单
+- **CAD图纸**：`design_[方案名].dxf` - 分层分色的拓扑图
+- **全部方案**：`[文件名]_result.zip` - 包含所有图纸及Excel报告
+
+## 关键常量和配置
+
+### 电气参数
+- **系统电压**：66,000 V (66kV)
+- **功率因数**：0.95
+- **电价**：0.4 元/kWh
+
+### 电缆规格示例
+- 最小截面：35mm² (载流量150A)
+- 最大截面：400mm² (载流量580A)
+- 降容系数：0.8（实际载流量 = 额定载流量 × 0.8）
+
+### 算法参数
+- 默认风机数量：30台
+- 默认布局：随机分布或网格
+- 默认间距：800米（网格布局）
+
+## 开发约定
+
+### 代码风格
+- 使用中文注释和文档字符串
+- 函数命名使用 snake_case
+- 类名使用 PascalCase
+- 常量使用 UPPER_CASE
+
+### 版本管理
+- 版本号通过 `make_version.py` 自动生成
+- 版本号格式：v{major}.{minor}.{patch}
+- 版本号存储在 `version.py` 文件中
+
+### 构建约定
+- 使用 `nicegui-pack` 进行打包
+- 单文件模式（--onefile）
+- 无窗口模式（--windowed）
+- 输出文件名包含版本号
+
+### 测试约定
+- GUI测试使用 frontend-tester agent
+- Python代码测试使用 python-pro agent
+- 测试覆盖率要求：核心算法部分 > 80%
+
+## 常见问题
+
+### Q1: MST算法显示极高的成本和损耗？
+**A**: 这是预期行为。MST算法不考虑载流量约束，会产生单一树状结构导致根部电缆严重过载。这仅作为理论基准参考。
+
+### Q2: 如何在CAD图纸中找到图形？
+**A**: 双击鼠标滚轮（Zoom Extents）全屏显示。风机坐标通常是大地坐标（数值很大），如果CAD当前视口在(0,0)附近，可能会找不到图形。
+
+### Q3: 可选电缆的使用规则是什么？
+**A**: 
+- 可选电缆（Optional='Y'）最多只能有一条
+- 必须是列表中截面最大的电缆
+- 用于特定场景（如增加单回路容量）
+
+## 技术支持
+
+- **适用对象**：海上能源业务开发部 - 电气专业
+- **技术支持**：杜孟远
+- **文档版本**：v1.0
+- **编制日期**：2026年1月5日
+
+## 许可证
+
+本项目仅供工程学习、研究和初步设计评估使用。详细计算应以专业设计院规范为准。

ga.py

@@ -0,0 +1,193 @@
+import numpy as np
+import pandas as pd
+from scipy.spatial import distance_matrix
+from scipy.sparse.csgraph import minimum_spanning_tree
+from collections import defaultdict
+import random
+
+
+def design_with_ga(
+    turbines,
+    substation,
+    cable_specs=None,
+    voltage=66000,
+    power_factor=0.95,
+    system_params=None,
+    pop_size=50,
+    generations=50,
+    evaluate_func=None,
+    total_invest_func=None,
+    get_max_capacity_func=None,
+):
+    """
+    使用遗传算法优化集电线路布局
+    :param turbines: 风机DataFrame
+    :param substation: 升压站坐标
+    :param cable_specs: 电缆规格
+    :param system_params: 系统参数（用于NPV计算）
+    :param pop_size: 种群大小
+    :param generations: 迭代代数
+    :param evaluate_func: 评估函数
+    :param total_invest_func: 总投资计算函数
+    :param get_max_capacity_func: 获取最大容量函数
+    :return: 连接列表和带有簇信息的turbines
+    """
+    if get_max_capacity_func:
+        max_mw = get_max_capacity_func(cable_specs, voltage, power_factor)
+    else:
+        max_mw = 100.0  # 默认值
+    total_power = turbines["power"].sum()
+    max_clusters = int(np.ceil(total_power / max_mw))
+    n_turbines = len(turbines)
+
+    # 预计算距离矩阵
+    all_coords = np.vstack([substation, turbines[["x", "y"]].values])
+    dist_matrix_full = distance_matrix(all_coords, all_coords)
+
+    def fitness(chromosome):
+        cluster_assign = chromosome
+        clusters = defaultdict(list)
+        for i, c in enumerate(cluster_assign):
+            clusters[c].append(i)
+
+        connections = []
+        for c, members in clusters.items():
+            if len(members) == 0:
+                continue
+            coords = turbines.iloc[members][["x", "y"]].values
+            if len(members) > 1:
+                dm = distance_matrix(coords, coords)
+                mst = minimum_spanning_tree(dm).toarray()
+                for i in range(len(members)):
+                    for j in range(len(members)):
+                        if mst[i, j] > 0:
+                            connections.append(
+                                (
+                                    f"turbine_{members[i]}",
+                                    f"turbine_{members[j]}",
+                                    mst[i, j],
+                                )
+                            )
+            # 连接到升压站
+            dists = [dist_matrix_full[0, m + 1] for m in members]
+            closest = members[np.argmin(dists)]
+            connections.append((f"turbine_{closest}", "substation", min(dists)))
+
+        eval_res = evaluate_func(
+            turbines,
+            connections,
+            substation,
+            cable_specs,
+            is_offshore=False,
+            method_name="GA",
+            voltage=voltage,
+            power_factor=power_factor,
+        )
+        if system_params and total_invest_func:
+            res_list = total_invest_func(
+                [
+                    {
+                        "cost": eval_res["total_cost"],
+                        "loss": eval_res["total_loss"],
+                        "eval": eval_res,
+                    }
+                ],
+                system_params,
+            )
+            return res_list[0]["total_cost_npv"]
+        return eval_res["total_cost"]
+
+    def init_individual():
+        assign = np.zeros(n_turbines, dtype=int)
+        cluster_powers = np.zeros(max_clusters)
+        for i in range(n_turbines):
+            p = turbines.iloc[i]["power"]
+            possible = [
+                c for c in range(max_clusters) if cluster_powers[c] + p <= max_mw
+            ]
+            if possible:
+                c = random.choice(possible)
+            else:
+                c = random.randint(0, max_clusters - 1)
+            assign[i] = c
+            cluster_powers[c] += p
+        return assign.tolist()
+
+    population = [init_individual() for _ in range(pop_size)]
+    best = None
+    best_fitness = float("inf")
+
+    for gen in range(generations):
+        fitnesses = [fitness(ind) for ind in population]
+        min_fit = min(fitnesses)
+        if min_fit < best_fitness:
+            best_fitness = min_fit
+            best = population[fitnesses.index(min_fit)].copy()
+
+        def tournament(size=3):
+            candidates = random.sample(list(zip(population, fitnesses)), size)
+            return min(candidates, key=lambda x: x[1])[0]
+
+        selected = [tournament() for _ in range(pop_size)]
+
+        new_pop = []
+        for i in range(0, pop_size, 2):
+            p1 = selected[i]
+            p2 = selected[i + 1] if i + 1 < pop_size else selected[0]
+            if random.random() < 0.8:
+                point = random.randint(1, n_turbines - 1)
+                child1 = p1[:point] + p2[point:]
+                child2 = p2[:point] + p1[point:]
+            else:
+                child1, child2 = p1.copy(), p2.copy()
+            new_pop.extend([child1, child2])
+
+        for ind in new_pop:
+            if random.random() < 0.1:
+                idx = random.randint(0, n_turbines - 1)
+                old_c = ind[idx]
+                new_c = random.randint(0, max_clusters - 1)
+                ind[idx] = new_c
+                cluster_powers = defaultdict(float)
+                for j, c in enumerate(ind):
+                    cluster_powers[c] += turbines.iloc[j]["power"]
+                if max(cluster_powers.values()) > max_mw:
+                    ind[idx] = max_clusters
+                    max_clusters += 1
+
+        elites = sorted(zip(population, fitnesses), key=lambda x: x[1])[
+            : int(0.1 * pop_size)
+        ]
+        new_pop[: len(elites)] = [e[0] for e in elites]
+        population = new_pop[:pop_size]
+
+    # 解码最佳个体
+    cluster_assign = best
+    clusters = defaultdict(list)
+    for i, c in enumerate(cluster_assign):
+        clusters[c].append(i)
+
+    connections = []
+    for c, members in clusters.items():
+        if len(members) == 0:
+            continue
+        coords = turbines.iloc[members][["x", "y"]].values
+        if len(members) > 1:
+            dm = distance_matrix(coords, coords)
+            mst = minimum_spanning_tree(dm).toarray()
+            for i in range(len(members)):
+                for j in range(len(members)):
+                    if mst[i, j] > 0:
+                        connections.append(
+                            (
+                                f"turbine_{members[i]}",
+                                f"turbine_{members[j]}",
+                                mst[i, j],
+                            )
+                        )
+        dists = [dist_matrix_full[0, m + 1] for m in members]
+        closest = members[np.argmin(dists)]
+        connections.append((f"turbine_{closest}", "substation", min(dists)))
+
+    turbines["cluster"] = cluster_assign
+    return connections, turbines

generate_template.py

@@ -38,15 +38,15 @@ def create_template(output_file='windfarm_template.xlsx'):
     
     # Create Cable data
     cable_data = [
-        {'CrossSection': 35, 'Capacity': 150, 'Resistance': 0.524, 'Cost': 80, 'Optional': ''},
-        {'CrossSection': 70, 'Capacity': 215, 'Resistance': 0.268, 'Cost': 120, 'Optional': ''},
-        {'CrossSection': 95, 'Capacity': 260, 'Resistance': 0.193, 'Cost': 150, 'Optional': ''},
-        {'CrossSection': 120, 'Capacity': 295, 'Resistance': 0.153, 'Cost': 180, 'Optional': ''},
-        {'CrossSection': 150, 'Capacity': 330, 'Resistance': 0.124, 'Cost': 220, 'Optional': ''},
-        {'CrossSection': 185, 'Capacity': 370, 'Resistance': 0.0991, 'Cost': 270, 'Optional': ''},
-        {'CrossSection': 240, 'Capacity': 425, 'Resistance': 0.0754, 'Cost': 350, 'Optional': ''},
-        {'CrossSection': 300, 'Capacity': 500, 'Resistance': 0.0601, 'Cost': 450, 'Optional': ''},
-        {'CrossSection': 400, 'Capacity': 580, 'Resistance': 0.0470, 'Cost': 600, 'Optional': ''}
+        {'CrossSection': 35, 'Capacity': 150, 'Resistance': 0.524, 'Cost': 8, 'Optional': ''},
+        {'CrossSection': 70, 'Capacity': 215, 'Resistance': 0.268, 'Cost': 12, 'Optional': ''},
+        {'CrossSection': 95, 'Capacity': 260, 'Resistance': 0.193, 'Cost': 15, 'Optional': ''},
+        {'CrossSection': 120, 'Capacity': 295, 'Resistance': 0.153, 'Cost': 18, 'Optional': ''},
+        {'CrossSection': 150, 'Capacity': 330, 'Resistance': 0.124, 'Cost': 22, 'Optional': ''},
+        {'CrossSection': 185, 'Capacity': 370, 'Resistance': 0.0991, 'Cost': 27, 'Optional': ''},
+        {'CrossSection': 240, 'Capacity': 425, 'Resistance': 0.0754, 'Cost': 35, 'Optional': ''},
+        {'CrossSection': 300, 'Capacity': 500, 'Resistance': 0.0601, 'Cost': 45, 'Optional': ''},
+        {'CrossSection': 400, 'Capacity': 580, 'Resistance': 0.0470, 'Cost': 60, 'Optional': ''}
     ]
     df_cables = pd.DataFrame(cable_data)
     
@@ -54,7 +54,10 @@ def create_template(output_file='windfarm_template.xlsx'):
     param_data = [
         {'Parameter': 'Voltage (kV) / 电压 (kV)', 'Value': 66},
         {'Parameter': 'Power Factor / 功率因数', 'Value': 0.95},
-        {'Parameter': 'Electricity Price (元/kWh) / 电价 (元/kWh)', 'Value': 0.4}
+        {'Parameter': 'Electricity Price (元/kWh) / 电价 (元/kWh)', 'Value': 0.4},
+        {'Parameter': 'Project Lifetime (years) / 工程运行期限/年', 'Value': 25},
+        {'Parameter': 'Discount Rate (%) / 折现率%', 'Value': 8},
+        {'Parameter': 'Annual Loss Hours (hours) / 年损耗小时数/小时', 'Value': 1400}
     ]
     df_params = pd.DataFrame(param_data)
     

gui.py

@@ -1,20 +1,25 @@
+import contextlib
+import io
 import os
 import sys
-import io
-import contextlib
 import tempfile
-import matplotlib.pyplot as plt
+
+import matplotlib
+
+matplotlib.use("Agg")
 import matplotlib.backends.backend_svg
-from nicegui import ui, events, app
+import matplotlib.pyplot as plt
+import pandas as pd
+from nicegui import app, events, ui, run
+
 from main import (
     compare_design_methods,
-    export_to_dxf,
-    load_data_from_excel,
-    generate_wind_farm_data,
-    visualize_design,
     export_all_scenarios_to_excel,
+    export_to_dxf,
+    generate_wind_farm_data,
+    load_data_from_excel,
+    visualize_design,
 )
-import pandas as pd
 
 # 尝试导入自动生成的版本号
 try:
@@ -85,6 +90,9 @@ def index():
         "run_btn": None,
         "current_file_container": None,  # 替换 label 为 container
         "info_container": None,  # 新增信息展示容器
+        "ga_switch": None,  # 遗传算法开关
+        "mip_switch": None,  # MIP开关
+        "log_content": "",  # 存储计算日志内容
     }
 
     def update_info_panel():
@@ -108,7 +116,7 @@ def index():
                         v = state["system_params"]["voltage"]
                         is_default_v = False
 
-                    v_str = f"电压: {v/1000:.1f} kV" if v >= 1000 else f"电压: {v} V"
+                    v_str = f"电压: {v / 1000:.1f} kV" if v >= 1000 else f"电压: {v} V"
                     if is_default_v:
                         v_str += " (默认)"
                     params_text.append(v_str)
@@ -143,6 +151,51 @@ def index():
                         ep_str += " (默认)"
                     params_text.append(ep_str)
 
+                    # 获取工程运行期限
+                    lifetime = 25  # Default
+                    is_default_lifetime = True
+                    if (
+                        state.get("system_params")
+                        and "project_lifetime" in state["system_params"]
+                    ):
+                        lifetime = state["system_params"]["project_lifetime"]
+                        is_default_lifetime = False
+
+                    lifetime_str = f"工程运行期限: {lifetime} 年"
+                    if is_default_lifetime:
+                        lifetime_str += " (默认)"
+                    params_text.append(lifetime_str)
+
+                    # 获取折现率
+                    discount_rate = 8  # Default
+                    is_default_discount = True
+                    if (
+                        state.get("system_params")
+                        and "discount_rate" in state["system_params"]
+                    ):
+                        discount_rate = state["system_params"]["discount_rate"]
+                        is_default_discount = False
+
+                    discount_str = f"折现率: {discount_rate}%"
+                    if is_default_discount:
+                        discount_str += " (默认)"
+                    params_text.append(discount_str)
+
+                    # 获取年损耗小时数
+                    annual_hours = 1400  # Default
+                    is_default_hours = True
+                    if (
+                        state.get("system_params")
+                        and "annual_loss_hours" in state["system_params"]
+                    ):
+                        annual_hours = state["system_params"]["annual_loss_hours"]
+                        is_default_hours = False
+
+                    hours_str = f"年损耗小时数: {annual_hours} 小时"
+                    if is_default_hours:
+                        hours_str += " (默认)"
+                    params_text.append(hours_str)
+
                     for p in params_text:
                         ui.chip(p, icon="bolt").props("outline color=primary")
 
@@ -175,7 +228,7 @@ def index():
                         },
                         {
                             "name": "cost",
-                            "label": "参考单价 (元/m)",
+                            "label": "参考单价(万元/km)",
                             "field": "cost",
                             "align": "center",
                         },
@@ -194,7 +247,9 @@ def index():
                                 "section": spec[0],
                                 "capacity": spec[1],
                                 "resistance": spec[2],
-                                "cost": spec[3],
+                                "cost": f"{spec[3] / 10:.2f}"
+                                if spec[3] is not None
+                                else "0.00",
                                 "is_optional": "Y" if len(spec) > 4 and spec[4] else "",
                             }
                         )
@@ -288,6 +343,16 @@ def index():
 
             update_info_panel()
 
+            # 清空方案对比结果和拓扑可视化
+            state["results"] = []
+            if refs["results_table"]:
+                refs["results_table"].rows = []
+                refs["results_table"].selected = []
+            if refs["plot_container"]:
+                refs["plot_container"].clear()
+            if refs["export_row"]:
+                refs["export_row"].clear()
+
             # 清空上传组件列表，以便下次选择（配合 .no-list CSS 使用）
             if refs["upload_widget"]:
                 refs["upload_widget"].reset()
@@ -295,7 +360,9 @@ def index():
         except Exception as ex:
             ui.notify(f"上传处理失败: {ex}", type="negative")
 
-    async def save_file_with_dialog(filename, callback, file_filter="All files (*.*)"):
+    async def save_file_with_dialog(
+        filename, callback, file_filter="All files (*.*)", sender=None
+    ):
         """
         跨平台文件保存助手。
         如果是原生模式，弹出系统保存对话框。
@@ -304,136 +371,84 @@ def index():
         :param filename: 默认文件名
         :param callback: 接收文件路径并执行保存操作的函数 (filepath) -> None
         :param file_filter: 格式如 "Excel Files (*.xlsx)"
+        :param sender: 触发该操作的 UI 组件，用于在操作期间禁用以防重复点击
         """
-        # 检测是否为原生模式 (PyWebview)
-        is_native = False
-        native_window = None
+        if sender:
+            sender.disable()
         try:
-            # 使用 getattr 安全获取 app.native，避免属性不存在错误
-            # 并在 reload=True 时 native 可能未能正确初始化
-            n_obj = getattr(app, "native", None)
-            if n_obj and getattr(n_obj, "main_window", None):
-                is_native = True
-                native_window = n_obj.main_window
-        except Exception as e:
-            print(f"DEBUG: Native check error: {e}")
+            # 方案：使用 PowerShell 弹出原生保存对话框 (仅限 Windows)
+            import platform
+            import subprocess
 
-        print(
-            f"DEBUG: save_file_with_dialog called. is_native={is_native}, filename={filename}"
-        )
-
-        if is_native and native_window:
-            try:
-                # PyWebview 的 create_file_dialog 的 file_types 参数期望一个字符串元组
-                # 格式如: ('Description (*.ext)', 'All files (*.*)')
-                file_types = (file_filter,)
-
-                print(f"DEBUG: calling create_file_dialog with types={file_types}")
-
-                # 在 Native 模式下，create_file_dialog 是同步阻塞的
-                # 注意：必须使用 app.native.SAVE_DIALOG
-                save_path = native_window.create_file_dialog(
-                    app.native.SAVE_DIALOG,
-                    directory="",
-                    save_filename=filename,
-                    file_types=file_types,
-                )
-
-                print(f"DEBUG: save_path result: {save_path}")
-
-                # 用户取消
-                if not save_path:
-                    return
-
-                # 处理返回类型 (PyWebview 可能返回字符串或列表)
-                if isinstance(save_path, (list, tuple)):
-                    if not save_path:
-                        return
-                    save_path = save_path[0]
-
-                # 确保文件名后缀正确
-                if not save_path.lower().endswith(
-                    os.path.splitext(filename)[1].lower()
-                ):
-                    save_path += os.path.splitext(filename)[1]
-
-                await callback(save_path)
-                ui.notify(f"文件已保存至: {save_path}", type="positive")
-                return  # 成功处理，退出
-
-            except Exception as e:
-                import traceback
-
-                traceback.print_exc()
-                print(f"ERROR in save_file_with_dialog (native): {e}")
-                # ui.notify(f"原生保存失败，尝试其他方式: {e}", type="warning")
-                print(f"原生保存失败，尝试其他方式: {e}")
-                # 继续向下执行，尝试 fallback
-
-        # 非 Native 模式 (或 Native 失败)，尝试使用 Tkinter (仅限本地环境)
-        try:
-            import tkinter as tk
-            from tkinter import filedialog
-            from nicegui import run
-
-            print("DEBUG: Attempting Tkinter dialog...")
-
-            def get_save_path_tk(default_name, f_filter):
+            if platform.system() == "Windows":
                 try:
-                    # 创建隐藏的根窗口
-                    root = tk.Tk()
-                    root.withdraw()
-                    root.attributes("-topmost", True)  # 尝试置顶
+                    # 构建 PowerShell 脚本
+                    # 注意：过滤器格式为 "描述|*.ext|所有文件|*.*"
+                    ps_filter = file_filter.replace("(", "|").replace(")", "")
+                    if "|" not in ps_filter:
+                        ps_filter += f"|{os.path.splitext(filename)[1] or '*.*'}"
 
-                    # 转换 filter 格式: "Excel Files (*.xlsx)" -> [("Excel Files", "*.xlsx")]
-                    filetypes = []
-                    if "(" in f_filter and ")" in f_filter:
-                        desc = f_filter.split("(")[0].strip()
-                        ext = f_filter.split("(")[1].split(")")[0]
-                        filetypes.append((desc, ext))
-                    filetypes.append(("All files", "*.*"))
+                    # 简单清洗 filter 字符串以适应 PowerShell (e.g., "Excel Files *.xlsx" -> "Excel Files|*.xlsx")
+                    # 这里做一个简化的映射，确保格式正确
+                    if "Excel" in file_filter:
+                        ps_filter = "Excel Files (*.xlsx)|*.xlsx|All Files (*.*)|*.*"
+                    elif "DXF" in file_filter:
+                        ps_filter = "DXF Files (*.dxf)|*.dxf|All Files (*.*)|*.*"
+                    elif "ZIP" in file_filter:
+                        ps_filter = "ZIP Archives (*.zip)|*.zip|All Files (*.*)|*.*"
+                    else:
+                        ps_filter = "All Files (*.*)|*.*"
 
-                    path = filedialog.asksaveasfilename(
-                        initialfile=default_name, filetypes=filetypes, title="保存文件"
+                    ps_script = f"""
+                    Add-Type -AssemblyName System.Windows.Forms
+                    $d = New-Object System.Windows.Forms.SaveFileDialog
+                    $d.Filter = "{ps_filter}"
+                    $d.FileName = "{filename}"
+                    $d.Title = "保存文件"
+                    if ($d.ShowDialog() -eq [System.Windows.Forms.DialogResult]::OK) {{
+                        Write-Output $d.FileName
+                    }}
+                    """
+
+                    # 运行 PowerShell
+                    # 使用 startupinfo 隐藏控制台窗口 (防止黑框闪烁)
+                    startupinfo = subprocess.STARTUPINFO()
+                    startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW
+
+                    print("DEBUG: invoking PowerShell SaveFileDialog...")
+
+                    # 使用 run.io_bound 在后台线程执行，避免阻塞主事件循环
+                    # 这样按钮的禁用状态可以立即同步到前端
+                    result = await run.io_bound(
+                        subprocess.run,
+                        ["powershell", "-Command", ps_script],
+                        capture_output=True,
+                        text=True,
+                        startupinfo=startupinfo,
                     )
-                    root.destroy()
-                    return path
-                except Exception as ex:
-                    print(f"Tkinter inner error: {ex}")
-                    return None
+                    save_path = result.stdout.strip()
+                    if save_path:
+                        print(f"DEBUG: PowerShell returned path: {save_path}")
+                        await callback(save_path)
+                        ui.notify(f"文件已保存至: {save_path}", type="positive")
+                        return
+                    else:
+                        print("DEBUG: PowerShell dialog cancelled or empty result.")
+                        # 用户取消，直接返回，不回退
+                        return
 
-            # 在线程中运行 tkinter，避免阻塞 asyncio 事件循环
-            save_path = await run.io_bound(get_save_path_tk, filename, file_filter)
+                except Exception as e:
+                    print(f"PowerShell dialog failed: {e}")
+                    # 出错则回退到 ui.download
 
-            if save_path:
-                print(f"DEBUG: Tkinter save_path: {save_path}")
-                # 确保文件名后缀正确
-                if not save_path.lower().endswith(
-                    os.path.splitext(filename)[1].lower()
-                ):
-                    save_path += os.path.splitext(filename)[1]
-
-                await callback(save_path)
-                ui.notify(f"文件已保存至: {save_path}", type="positive")
-                return  # 成功处理
-            elif save_path is None:
-                print("DEBUG: Tkinter dialog cancelled or failed silently.")
-                # 如果是用户取消（返回空字符串），通常不需要回退到下载。
-                # 但这里如果 Tkinter 彻底失败返回 None，可能需要回退。
-                # askopenfilename 返回空字符串表示取消。我们假设 None 是异常。
-                # 这里简化处理：只要没拿到路径且没报错，就认为是取消。
-                if save_path == "":
-                    return
-
-        except Exception as e:
-            print(f"Tkinter dialog failed: {e}")
-            # Fallback to ui.download if tkinter fails
-
-        # 最后的回退方案：浏览器下载
-        print("DEBUG: Falling back to ui.download")
-        temp_path = os.path.join(state["temp_dir"], filename)
-        await callback(temp_path)
-        ui.download(temp_path)
+            # 统一回退方案：浏览器下载
+            print("DEBUG: Using ui.download fallback")
+            temp_path = os.path.join(state["temp_dir"], filename)
+            await callback(temp_path)
+            ui.download(temp_path)
+        finally:
+            if sender:
+                sender.enable()
 
     def update_export_buttons():
         if refs["export_row"]:
@@ -464,7 +479,6 @@ def index():
             best_res = min(state["results"], key=lambda x: x["cost"])
 
         with refs["export_row"]:
-
             # --- 下载 Excel ---
             async def save_excel(path):
                 import shutil
@@ -476,9 +490,12 @@ def index():
                     # 如果不存在，重新生成
                     export_all_scenarios_to_excel(state["results"], path)
 
-            async def on_click_excel():
+            async def on_click_excel(e):
                 await save_file_with_dialog(
-                    default_excel_name, save_excel, "Excel Files (*.xlsx)"
+                    default_excel_name,
+                    save_excel,
+                    "Excel Files (*.xlsx)",
+                    sender=e.sender,
                 )
 
             ui.button(
@@ -487,41 +504,7 @@ def index():
             ).props("icon=download")
 
             # --- 导出推荐方案 DXF ---
-            def export_best_dxf():
-                if state["substation"] is not None:
-                    safe_name = "".join(
-                        [
-                            c
-                            for c in best_res["name"]
-                            if c.isalnum() or c in (" ", "-", "_")
-                        ]
-                    ).strip()
-                    default_name = f"{file_prefix}_best_{safe_name}.dxf"
-
-                    async def save_dxf(path):
-                        export_to_dxf(
-                            best_res["turbines"],
-                            state["substation"],
-                            best_res["eval"]["details"],
-                            path,
-                        )
-
-                    # 包装为 async 任务，并在 NiceGUI 事件循环中执行
-                    async def run_save():
-                        await save_file_with_dialog(
-                            default_name, save_dxf, "DXF Files (*.dxf)"
-                        )
-
-                    # 这里的 export_best_dxf 本身是普通函数，绑定到 on_click
-                    # 但我们需要它执行异步操作。最简单的是让 export_best_dxf 变为 async
-                    # 或者在这里直接调用 run_save (但这在普通函数里不行)
-                    # 更好的方法是将 export_best_dxf 定义为 async，如下所示
-                    return run_save()
-                else:
-                    ui.notify("缺少升压站数据，无法导出 DXF", type="negative")
-
-            # 将 export_best_dxf 改为 async 并重命名，以便直接用作回调
-            async def on_click_best_dxf():
+            async def on_click_best_dxf(e):
                 if state["substation"] is not None:
                     safe_name = "".join(
                         [
@@ -541,17 +524,17 @@ def index():
                         )
 
                     await save_file_with_dialog(
-                        default_name, save_dxf, "DXF Files (*.dxf)"
+                        default_name, save_dxf, "DXF Files (*.dxf)", sender=e.sender
                     )
                 else:
                     ui.notify("缺少升压站数据，无法导出 DXF", type="negative")
 
             ui.button(
-                f'导出推荐方案 DXF ({best_res["name"]})', on_click=on_click_best_dxf
+                f"导出推荐方案 DXF ({best_res['name']})", on_click=on_click_best_dxf
             ).props("icon=architecture color=accent")
 
             # --- 导出选中方案 DXF ---
-            async def on_click_selected_dxf():
+            async def on_click_selected_dxf(e):
                 if not refs["results_table"] or not refs["results_table"].selected:
                     ui.notify("请先在上方表格中选择一个方案", type="warning")
                     return
@@ -581,7 +564,7 @@ def index():
                         )
 
                     await save_file_with_dialog(
-                        default_name, save_dxf, "DXF Files (*.dxf)"
+                        default_name, save_dxf, "DXF Files (*.dxf)", sender=e.sender
                     )
                 else:
                     ui.notify(
@@ -596,7 +579,7 @@ def index():
             refs["export_selected_btn"].set_text(f"导出选中方案 ({clean_name})")
 
             # --- 导出全部 ZIP ---
-            async def on_click_all_dxf():
+            async def on_click_all_dxf(e):
                 if not state["results"] or state["substation"] is None:
                     ui.notify("无方案数据可导出", type="warning")
                     return
@@ -642,19 +625,78 @@ def index():
                             except:
                                 pass
 
-                await save_file_with_dialog(default_name, save_zip, "ZIP Files (*.zip)")
+                await save_file_with_dialog(
+                    default_name, save_zip, "ZIP Files (*.zip)", sender=e.sender
+                )
 
             ui.button("导出全部方案 DXF (ZIP)", on_click=on_click_all_dxf).props(
                 "icon=folder_zip color=secondary"
             )
 
+            # --- 导出计算日志 ---
+            async def on_click_export_log(e):
+                # 尝试多种方式获取日志内容
+                log_content = ""
+                method_used = "unknown"
+
+                # 方法1: 首先尝试从保存的日志内容获取
+                if refs.get("log_content") and refs["log_content"].strip():
+                    log_content = refs["log_content"]
+                    method_used = "saved_memory"
+
+                # 方法2: 如果保存的日志为空，尝试使用 JavaScript 获取 log 组件的内容
+                if not log_content.strip() and refs["log_box"]:
+                    try:
+                        log_id = refs["log_box"].id
+                        js_code = f"""
+                        (function() {{
+                            const logElement = document.querySelector("#c{log_id}");
+                            if (logElement) {{
+                                console.log("Found log element:", logElement);
+                                return logElement.innerText || logElement.textContent || "";
+                            }}
+                            console.log("Log element not found for ID: c{log_id}");
+                            return "";
+                        }})()
+                        """
+                        result = await ui.run_javascript(js_code)
+                        if result and result.strip():
+                            log_content = result
+                            method_used = "javascript"
+                    except Exception as js_error:
+                        print(f"JavaScript method failed: {js_error}")
+
+                if not log_content.strip():
+                    ui.notify(
+                        "没有可导出的日志内容。请先运行计算任务。", type="warning"
+                    )
+                    print(f"Log export failed. Method tried: {method_used}")
+                    return
+
+                print(
+                    f"Successfully exported log using method: {method_used}, length: {len(log_content)}"
+                )
+                default_name = f"{file_prefix}_calculation_log.txt"
+
+                async def save_log(path):
+                    with open(path, "w", encoding="utf-8") as f:
+                        f.write(log_content)
+
+                await save_file_with_dialog(
+                    default_name, save_log, "Text Files (*.txt)", sender=e.sender
+                )
+
+            ui.button("导出计算日志", on_click=on_click_export_log).props(
+                "icon=description color=info"
+            )
+
     def update_plot(result):
         if refs["plot_container"]:
             refs["plot_container"].clear()
             with refs["plot_container"]:
                 # 使用 ui.pyplot 上下文自动管理 figure 生命周期
                 with ui.pyplot(figsize=(10, 8)) as plot:
-                    title = f"{result['name']}\nCost: ¥{result['cost']/10000:.2f}万 | Loss: {result['loss']:.2f} kW"
+                    title = f"{result['name']}\nCost: ¥{result['cost'] / 10000:.2f}万 | Loss: {result['loss']:.2f} kW"
                     # 显式获取当前 ui.pyplot 创建的 axes，并传递给绘图函数
                     # 确保绘图发生在正确的 figure 上
                     ax = plt.gca()
@@ -694,7 +736,6 @@ def index():
                 clean_name = row_name.replace("(推荐) ", "")
                 refs["export_selected_btn"].set_text(f"导出选中方案 ({clean_name})")
 
-    from nicegui import run
     import queue
 
     async def run_analysis():
@@ -703,8 +744,15 @@ def index():
             return
         if refs["log_box"]:
             refs["log_box"].clear()
+        # 重置日志内容
+        refs["log_content"] = ""
         log_queue = queue.Queue()
 
+        # 获取开关状态
+        use_ga = refs["ga_switch"].value if refs["ga_switch"] else False
+        use_mip = refs["mip_switch"].value if refs["mip_switch"] else False
+        print(f"Switch values: GA={use_ga}, MIP={use_mip}")
+
         class QueueLogger(io.StringIO):
             def write(self, message):
                 if message and message.strip():
@@ -718,13 +766,15 @@ def index():
                     try:
                         msg = log_queue.get_nowait()
                         refs["log_box"].push(msg)
+                        # 同时保存到日志内容中
+                        refs["log_content"] += msg + "\n"
                         new_msg = True
                         if msg.startswith("--- Scenario"):
                             scenario_name = msg.replace("---", "").strip()
                             if refs["status_label"]:
-                                refs["status_label"].text = (
-                                    f"正在计算: {scenario_name}..."
-                                )
+                                refs[
+                                    "status_label"
+                                ].text = f"正在计算: {scenario_name}..."
                         elif "开始比较电缆方案" in msg:
                             if refs["status_label"]:
                                 refs["status_label"].text = "准备开始计算..."
@@ -752,6 +802,8 @@ def index():
                         n_clusters_override=None,
                         interactive=False,
                         plot_results=False,
+                        use_ga=use_ga,
+                        use_mip=use_mip,
                     )
 
             # 在后台线程运行计算任务
@@ -777,7 +829,7 @@ def index():
 
                 update_plot(best_res)
                 ui.notify(
-                    f'计算完成！已自动加载推荐方案: {best_res["name"]}', type="positive"
+                    f"计算完成！已自动加载推荐方案: {best_res['name']}", type="positive"
                 )
 
             # 更新结果表格
@@ -813,14 +865,25 @@ def index():
                     elif "No Max" in original_name:
                         note += "不包含可选电缆型号，且可使用的最大截面电缆降一档截面。"
 
-                    # 计算总长度
-                    total_length = sum(d["length"] for d in res["eval"]["details"])
+                    # 计算总长度（转换为公里）
+                    total_length_m = sum(d["length"] for d in res["eval"]["details"])
+                    total_length_km = total_length_m / 1000
+
+                    # 获取回路数 (通过统计从升压站发出的连接)
+                    n_circuits = sum(
+                        1
+                        for d in res["eval"]["details"]
+                        if d["source"] == "substation" or d["target"] == "substation"
+                    )
 
                     row_dict = {
                         "name": name_display,
+                        "n_circuits": n_circuits,
                         "cost_wan": f"{res['cost'] / 10000:.2f}",
                         "loss_kw": f"{res['loss']:.2f}",
-                        "total_length": f"{total_length:.2f}",
+                        "total_length": f"{total_length_km:.2f}",
+                        "npv_loss_wan": f"{res.get('npv_loss', 0) / 10000:.2f}",
+                        "total_cost_npv_wan": f"{res.get('total_cost_npv', res['cost']) / 10000:.2f}",
                         "note": note,
                         "original_name": res["name"],
                     }
@@ -879,16 +942,20 @@ def index():
     with ui.row().classes("w-full p-4 gap-4"):
         with ui.card().classes("w-full p-4 shadow-md"):
             ui.label("配置面板").classes("text-xl font-semibold mb-4 border-b pb-2")
-            
+
             # 使用 items-stretch 确保所有子元素高度一致
-            with ui.row().classes('w-full items-stretch gap-4'):
+            with ui.row().classes("w-full items-stretch gap-4"):
                 # 1. 导出模板按钮
-                async def export_template():
-                    from generate_template import create_template
+                async def export_template(e):
                     import shutil
+
+                    from generate_template import create_template
+
                     async def save_template(path):
                         # 生成模板到系统临时目录
-                        temp_template = os.path.join(state["temp_dir"], "coordinates_template.xlsx")
+                        temp_template = os.path.join(
+                            state["temp_dir"], "coordinates_template.xlsx"
+                        )
                         create_template(temp_template)
                         if os.path.exists(temp_template):
                             shutil.copy2(temp_template, path)
@@ -900,9 +967,10 @@ def index():
                             raise FileNotFoundError("无法生成模板文件")
 
                     await save_file_with_dialog(
-                        "coordinates.xlsx", 
-                        save_template, 
-                        "Excel Files (*.xlsx)"
+                        "coordinates.xlsx",
+                        save_template,
+                        "Excel Files (*.xlsx)",
+                        sender=e.sender,
                     )
 
                 ui.button("导出 Excel 模板", on_click=export_template).classes(
@@ -910,12 +978,18 @@ def index():
                 ).props("icon=file_download outline color=primary")
 
                 # 2. 上传文件区域 (垂直堆叠 Label 和 Upload 组件)
-                with ui.column().classes('flex-1 gap-0 justify-between'):
+                with ui.column().classes("flex-1 gap-0 justify-between"):
                     # 使用 .no-list CSS 隐藏 Quasar 默认列表，完全自定义文件显示
-                    refs["upload_widget"] = ui.upload(
-                        label="选择Excel文件", on_upload=handle_upload, auto_upload=True
-                    ).classes("w-full no-list h-full").props('flat bordered color=primary')
-                    
+                    refs["upload_widget"] = (
+                        ui.upload(
+                            label="选择Excel文件",
+                            on_upload=handle_upload,
+                            auto_upload=True,
+                        )
+                        .classes("w-full no-list h-full")
+                        .props("flat bordered color=primary")
+                    )
+
                     # 自定义文件显示容器
                     refs["current_file_container"] = ui.column().classes("w-full")
                     # 初始状态不显示任何内容，直到选择文件后才显示
@@ -931,6 +1005,17 @@ def index():
                     .classes("flex-1 py-4")
                     .props("icon=play_arrow color=secondary")
                 )
+                # 4. 遗传算法开关
+                with ui.column().classes("flex-1 gap-0 justify-center items-center"):
+                    refs["ga_switch"] = ui.switch("启用遗传算法", value=False).props(
+                        "color=orange"
+                    )
+
+                # 5. MIP开关
+                with ui.column().classes("flex-1 gap-0 justify-center items-center"):
+                    refs["mip_switch"] = ui.switch("启用MIP", value=False).props(
+                        "color=blue"
+                    )
 
         with ui.column().classes("w-full gap-4"):
             # 新增：信息展示卡片
@@ -946,9 +1031,15 @@ def index():
                     )
 
             with ui.card().classes("w-full p-0 shadow-md overflow-hidden"):
-                with ui.expansion(
-                    "方案对比结果 (点击行查看拓扑详情)", icon="analytics", value=True
-                ).classes("w-full").props("header-class=\"text-xl font-semibold\""):
+                with (
+                    ui.expansion(
+                        "方案对比结果 (点击行查看拓扑详情)",
+                        icon="analytics",
+                        value=True,
+                    )
+                    .classes("w-full")
+                    .props('header-class="text-xl font-semibold"')
+                ):
                     columns = [
                         {
                             "name": "name",
@@ -957,30 +1048,49 @@ def index():
                             "required": True,
                             "align": "left",
                         },
+                        {
+                            "name": "n_circuits",
+                            "label": "回路数",
+                            "field": "n_circuits",
+                            "sortable": True,
+                        },
                         {
                             "name": "cost_wan",
                             "label": "总投资 (万元)",
                             "field": "cost_wan",
                             "sortable": True,
                         },
-                                            {
-                                                "name": "loss_kw",
-                                                "label": "线损 (kW)",
-                                                "field": "loss_kw",
-                                                "sortable": True,
-                                            },
-                                            {
-                                                "name": "total_length",
-                                                "label": "总长度 (m)",
-                                                "field": "total_length",
-                                                "sortable": True,
-                                            },
-                                            {
-                                                "name": "note",
-                                                "label": "备注",
-                                                "field": "note",
-                                                "align": "left",
-                                            },                    ]
+                        {
+                            "name": "loss_kw",
+                            "label": "线损 (kW)",
+                            "field": "loss_kw",
+                            "sortable": True,
+                        },
+                        {
+                            "name": "total_length",
+                            "label": "总长度/km",
+                            "field": "total_length",
+                            "sortable": True,
+                        },
+                        {
+                            "name": "npv_loss_wan",
+                            "label": "损耗费用净现值 (万元)",
+                            "field": "npv_loss_wan",
+                            "sortable": True,
+                        },
+                        {
+                            "name": "total_cost_npv_wan",
+                            "label": "总费用 (万元)",
+                            "field": "total_cost_npv_wan",
+                            "sortable": True,
+                        },
+                        {
+                            "name": "note",
+                            "label": "备注",
+                            "field": "note",
+                            "align": "left",
+                        },
+                    ]
                     # 使用内置的 selection='single' 结合行点击事件实现背景高亮
                     # 这样可以完全由 Python 事件逻辑控制，不依赖 CSS 伪类
                     refs["results_table"] = ui.table(
@@ -1055,12 +1165,18 @@ if getattr(sys, "frozen", False):
     )
 else:
     # 普通使用环境保留日志功能
-    ui.run(title="海上风电场集电线路优化", host='127.0.0.1', reload=True, port=target_port, native=False)
     # ui.run(
     #     title="海上风电场集电线路优化",
     #     host="127.0.0.1",
-    #     port=target_port,
     #     reload=True,
-    #     window_size=(1280, 800),
-    #     native=True,
+    #     port=target_port,
+    #     native=False,
     # )
+    ui.run(
+        title="海上风电场集电线路优化",
+        host="127.0.0.1",
+        port=target_port,
+        reload=True,
+        window_size=(1280, 800),
+        native=True,
+    )

mip.py

@@ -0,0 +1,472 @@
+import numpy as np
+import pandas as pd
+from scipy.spatial import distance_matrix
+from scipy.sparse.csgraph import minimum_spanning_tree
+from collections import defaultdict
+import random
+
+try:
+    import pulp
+
+    pulp_available = True
+except ImportError:
+    pulp = None
+    pulp_available = False
+
+try:
+    import pyomo.environ as pyo_env
+
+    pyomo_available = True
+except (ImportError, AttributeError):
+    pyomo_available = False
+    print("Pyomo not available, falling back to PuLP")
+
+
+def design_with_pyomo(
+    turbines,
+    substation,
+    cable_specs=None,
+    voltage=66000,
+    power_factor=0.95,
+    system_params=None,
+    max_clusters=None,
+    time_limit=300,
+    evaluate_func=None,
+    total_invest_func=None,
+    get_max_capacity_func=None,
+):
+    """
+    使用Pyomo求解器优化集电线路布局
+    :param turbines: 风机DataFrame
+    :param substation: 升压站坐标
+    :param cable_specs: 电缆规格
+    :param system_params: 系统参数（用于NPV计算）
+    :param max_clusters: 最大簇数，默认基于功率计算
+    :param time_limit: 求解时间限制（秒）
+    :param evaluate_func: 评估函数
+    :param total_invest_func: 总投资计算函数
+    :param get_max_capacity_func: 获取最大容量函数
+    :return: 连接列表和带有簇信息的turbines
+    """
+    if get_max_capacity_func:
+        max_mw = get_max_capacity_func(cable_specs, voltage, power_factor)
+    else:
+        max_mw = 100.0
+    total_power = turbines["power"].sum()
+    if max_clusters is None:
+        max_clusters = int(np.ceil(total_power / max_mw))
+    n_turbines = len(turbines)
+
+    all_coords = np.vstack([substation, turbines[["x", "y"]].values])
+    dist_matrix_full = distance_matrix(all_coords, all_coords)
+
+    # Simple fallback for now - use PuLP instead
+    print("Pyomo not fully implemented, falling back to PuLP")
+    return design_with_mip(
+        turbines,
+        substation,
+        cable_specs,
+        voltage,
+        power_factor,
+        system_params,
+        max_clusters,
+        time_limit,
+        evaluate_func,
+        total_invest_func,
+        get_max_capacity_func,
+    )
+
+
+def design_with_mip(
+    turbines,
+    substation,
+    cable_specs=None,
+    voltage=66000,
+    power_factor=0.95,
+    system_params=None,
+    max_clusters=None,
+    time_limit=300,
+    evaluate_func=None,
+    total_invest_func=None,
+    get_max_capacity_func=None,
+):
+    """
+    使用混合整数规划(MIP)优化集电线路布局
+    :param turbines: 风机DataFrame
+    :param substation: 升压站坐标
+    :param cable_specs: 电缆规格
+    :param system_params: 系统参数（用于NPV计算）
+    :param max_clusters: 最大簇数，默认基于功率计算
+    :param time_limit: 求解时间限制（秒）
+    :param evaluate_func: 评估函数
+    :param total_invest_func: 总投资计算函数
+    :param get_max_capacity_func: 获取最大容量函数
+    :return: 连接列表和带有簇信息的turbines
+    """
+    if not pulp_available:
+        print(
+            "WARNING: PuLP library not available. MIP optimization skipped, falling back to MST."
+        )
+        from main import design_with_mst
+
+        connections = design_with_mst(turbines, substation)
+        return connections, turbines
+
+    if get_max_capacity_func:
+        max_mw = get_max_capacity_func(cable_specs, voltage, power_factor)
+    else:
+        max_mw = 100.0
+    if max_clusters is None:
+        max_clusters = int(np.ceil(turbines["power"].sum() / max_mw))
+    n_turbines = len(turbines)
+
+    print(
+        f"MIP Model Setup: n_turbines={n_turbines}, max_clusters={max_clusters}, max_mw={max_mw:.2f} MW"
+    )
+
+    all_coords = np.vstack([substation, turbines[["x", "y"]].values])
+    dist_matrix_full = distance_matrix(all_coords, all_coords)
+
+    prob = pulp.LpProblem("WindFarmCollectorMIP", pulp.LpMinimize)
+
+    # Create all decision variables upfront to avoid duplicates
+    assign_vars = {}
+    for i in range(n_turbines):
+        for k in range(max_clusters):
+            assign_vars[(i, k)] = pulp.LpVariable(f"assign_{i}_{k}", cat="Binary")
+
+    cluster_vars = {}
+    for k in range(max_clusters):
+        cluster_vars[k] = pulp.LpVariable(f"cluster_{k}", cat="Binary")
+
+    # Helper functions to access variables
+    def assign_var(i, k):
+        return assign_vars[(i, k)]
+
+    def cluster_var(k):
+        return cluster_vars[k]
+
+    # Simplified objective function: minimize total distance
+    prob += pulp.lpSum(
+        [
+            dist_matrix_full[0, i + 1] * assign_var(i, k)
+            for i in range(n_turbines)
+            for k in range(max_clusters)
+        ]
+    )
+
+    for i in range(n_turbines):
+        prob += pulp.lpSum([assign_var(i, k) for k in range(max_clusters)]) == 1
+
+    for k in range(max_clusters):
+        cluster_power = pulp.lpSum(
+            [turbines.iloc[i]["power"] * assign_var(i, k) for i in range(n_turbines)]
+        )
+        prob += cluster_power <= max_mw * 1.2 * cluster_var(k)
+
+    for k in range(max_clusters):
+        for i in range(n_turbines):
+            prob += assign_var(i, k) <= cluster_var(k)
+
+    print(
+        f"MIP Model: {len(prob.variables())} variables, {len(prob.constraints)} constraints"
+    )
+
+    # Debug: Print model structure
+    print("MIP model structure check:")
+    print(f"  Variables: {len(prob.variables())}")
+    print(f"  Constraints: {len(prob.constraints)}")
+    print(f"  Time limit: {time_limit}s")
+    print(f"  Turbines: {n_turbines}, Clusters: {max_clusters}")
+
+    # Test solver availability
+    try:
+        import subprocess
+
+        test_solver = subprocess.run(
+            [
+                r"D:\code\windfarm\.venv\Lib\site-packages\pulp\apis\..\solverdir\cbc\win\i64\cbc.exe",
+                "-version",
+            ],
+            capture_output=True,
+            text=True,
+            timeout=5,
+        )
+        print(
+            f"CBC solver test: {test_solver.stdout[:100] if test_solver.stdout else 'No output'}"
+        )
+    except Exception as solver_test_error:
+        print(f"CBC solver test failed: {solver_test_error}")
+
+    print("MIP: Starting to solve...")
+    try:
+        # Try to use CBC solver with different configurations
+        solver = pulp.PULP_CBC_CMD(
+            timeLimit=time_limit,
+            msg=False,
+            warmStart=False,
+        )
+        print(f"Using CBC solver with time limit: {time_limit}s")
+        status = prob.solve(solver)
+        print(
+            f"MIP: Solver status={pulp.LpStatus[prob.status]}, Objective value={pulp.value(prob.objective):.4f}"
+        )
+    except Exception as e:
+        print(f"MIP: CBC solver execution failed: {e}")
+        # Try alternative solver configurations
+        try:
+            print("MIP: Trying alternative solver configuration...")
+            solver = pulp.PULP_CBC_CMD(
+                msg=True,  # Enable messages for debugging
+                threads=1,  # Single thread
+                timeLimit=time_limit,
+            )
+            status = prob.solve(solver)
+            print(
+                f"MIP: Alternative solver status={pulp.LpStatus[prob.status]}, Objective value={pulp.value(prob.objective):.4f}"
+            )
+        except Exception as e2:
+            print(f"MIP: All solver attempts failed: {e2}, falling back to MST")
+            from main import design_with_mst
+
+            connections = design_with_mst(turbines, substation)
+            return connections, turbines
+
+    if pulp.LpStatus[prob.status] != "Optimal":
+        print(
+            f"MIP solver status: {pulp.LpStatus[prob.status]}, solution not found, falling back to MST"
+        )
+        print("Model feasibility check:")
+        print(f"Total power: {turbines['power'].sum():.2f} MW")
+        print(f"Max cluster capacity: {max_mw:.2f} MW")
+        print(f"Number of clusters: {max_clusters}, Number of turbines: {n_turbines}")
+
+        for k in range(max_clusters):
+            cluster_power = pulp.value(
+                pulp.lpSum(
+                    [
+                        turbines.iloc[i]["power"] * assign_var(i, k)
+                        for i in range(n_turbines)
+                    ]
+                )
+            )
+            cluster_used = pulp.value(cluster_var(k))
+            print(
+                f"Cluster {k}: Power={cluster_power:.2f} MW (max {max_mw * 1.2:.2f}), Used={cluster_used}"
+            )
+
+        from main import design_with_mst
+
+        connections = design_with_mst(turbines, substation)
+        return connections, turbines
+
+    cluster_assign = [-1] * n_turbines
+    active_clusters = []
+    for k in range(max_clusters):
+        if pulp.value(cluster_var(k)) > 0.5:
+            active_clusters.append(k)
+
+    for i in range(n_turbines):
+        assigned = False
+        for k in active_clusters:
+            if pulp.value(assign_var(i, k)) > 0.5:
+                cluster_assign[i] = k
+                assigned = True
+                break
+        if not assigned:
+            dists = [dist_matrix_full[0, i + 1] for k in active_clusters]
+            cluster_assign[i] = active_clusters[np.argmin(dists)]
+
+    clusters = defaultdict(list)
+    for i, c in enumerate(cluster_assign):
+        clusters[c].append(i)
+
+    connections = []
+    for c, members in clusters.items():
+        if len(members) == 0:
+            continue
+        coords = turbines.iloc[members][["x", "y"]].values
+        if len(members) > 1:
+            dm = distance_matrix(coords, coords)
+            mst = minimum_spanning_tree(dm).toarray()
+            for i in range(len(members)):
+                for j in range(len(members)):
+                    if mst[i, j] > 0:
+                        connections.append(
+                            (
+                                f"turbine_{members[i]}",
+                                f"turbine_{members[j]}",
+                                mst[i, j],
+                            )
+                        )
+        dists = [dist_matrix_full[0, m + 1] for m in members]
+        closest = members[np.argmin(dists)]
+        connections.append((f"turbine_{closest}", "substation", min(dists)))
+
+    turbines["cluster"] = cluster_assign
+
+    # Check cluster distances
+    min_cluster_distance = check_cluster_distances(clusters, turbines)
+    if min_cluster_distance is not None:
+        print(
+            f"Cluster validation: Minimum distance between clusters = {min_cluster_distance:.2f} m"
+        )
+        if min_cluster_distance < 1000:
+            print(
+                f"WARNING: Clusters are very close to each other ({min_cluster_distance:.2f} m < 1000 m)"
+            )
+        elif min_cluster_distance < 2000:
+            print(
+                f"NOTICE: Clusters are relatively close ({min_cluster_distance:.2f} m)"
+            )
+
+    # Check for cable crossings
+    cable_crossings = check_cable_crossings(connections, turbines, substation)
+    if cable_crossings:
+        print(
+            f"WARNING: Found {len(cable_crossings)} cable crossing(s) in the solution"
+        )
+        for i, (idx1, idx2, p1, p2, p3, p4) in enumerate(cable_crossings):
+            conn1 = connections[idx1]
+            conn2 = connections[idx2]
+            print(
+                f"  Crossing {i + 1}: Connection {conn1[0]}-{conn1[1]} crosses {conn2[0]}-{conn2[1]}"
+            )
+    else:
+        print("No cable crossings detected in the solution")
+
+    print(
+        f"MIP optimization completed successfully, {len(connections)} connections generated"
+    )
+    return connections, turbines
+
+
+def calculate_cluster_centroids(clusters, turbines):
+    """Calculate the centroid coordinates for each cluster."""
+    centroids = {}
+    for c, members in clusters.items():
+        if len(members) == 0:
+            centroids[c] = (0, 0)
+        else:
+            coords = turbines.iloc[members][["x", "y"]].values
+            centroid_x = np.mean(coords[:, 0])
+            centroid_y = np.mean(coords[:, 1])
+            centroids[c] = (centroid_x, centroid_y)
+    return centroids
+
+
+def check_cluster_distances(clusters, turbines, min_distance_threshold=1000):
+    """Check if any clusters are too close to each other."""
+    if len(clusters) < 2:
+        return None
+
+    centroids = calculate_cluster_centroids(clusters, turbines)
+    active_clusters = [c for c, members in clusters.items() if len(members) > 0]
+
+    min_distance = float("inf")
+    min_pair = None
+
+    for i in range(len(active_clusters)):
+        for j in range(i + 1, len(active_clusters)):
+            c1, c2 = active_clusters[i], active_clusters[j]
+            centroid1 = np.array(centroids[c1])
+            centroid2 = np.array(centroids[c2])
+            distance = np.linalg.norm(centroid1 - centroid2)
+
+            if distance < min_distance:
+                min_distance = distance
+                min_pair = (c1, c2)
+
+    return min_distance
+
+
+def check_cable_crossings(connections, turbines, substation):
+    """Check if there are cable crossings in the solution."""
+    crossings = []
+
+    def line_intersection(p1, p2, p3, p4):
+        """Check if line segments (p1,p2) and (p3,p4) intersect."""
+        x1, y1 = p1
+        x2, y2 = p2
+        x3, y3 = p3
+        x4, y4 = p4
+
+        denom = (y4 - y3) * (x2 - x1) - (x4 - x3) * (y2 - y1)
+
+        if abs(denom) < 1e-10:
+            return False
+
+        ua = ((x4 - x3) * (y1 - y3) - (y4 - y3) * (x1 - x3)) / denom
+        ub = ((x2 - x1) * (y1 - y3) - (y2 - y1) * (x1 - x3)) / denom
+
+        return 0 <= ua <= 1 and 0 <= ub <= 1
+
+    def get_turbine_coord(connection_part):
+        """Get coordinates from connection part (turbine_# or substation)."""
+        if connection_part == "substation":
+            # Handle different substation formats robustly
+            if isinstance(substation, np.ndarray):
+                if substation.ndim == 1:
+                    # 1D array [x, y]
+                    return (substation[0], substation[1])
+                elif substation.ndim == 2:
+                    # 2D array [[x, y]] or shape (n, 2)
+                    if substation.shape[0] == 1:
+                        return (substation[0, 0], substation[0, 1])
+                    else:
+                        # Multiple points, use first one
+                        return (substation[0, 0], substation[0, 1])
+                else:
+                    # Unexpected dimension, try fallback
+                    return (substation.flat[0], substation.flat[1])
+            elif isinstance(substation, (list, tuple)):
+                # List or tuple format
+                # Handle nested lists like [[x, y]]
+                if (
+                    isinstance(substation[0], (list, tuple, np.ndarray))
+                    and len(substation[0]) >= 2
+                ):
+                    return (substation[0][0], substation[0][1])
+                elif len(substation) >= 2:
+                    return (substation[0], substation[1])
+                else:
+                    return (float("inf"), float("inf"))
+            else:
+                # Unexpected format, try to convert
+                try:
+                    sub_array = np.array(substation)
+                    if sub_array.ndim == 1:
+                        return (sub_array[0], sub_array[1])
+                    else:
+                        return (sub_array.flat[0], sub_array.flat[1])
+                except:
+                    return (float("inf"), float("inf"))
+        else:
+            turbine_idx = int(connection_part.split("_")[1])
+            return (
+                turbines.iloc[turbine_idx]["x"],
+                turbines.iloc[turbine_idx]["y"],
+            )
+
+    for i in range(len(connections)):
+        for j in range(i + 1, len(connections)):
+            conn1 = connections[i]
+            conn2 = connections[j]
+
+            p1 = get_turbine_coord(conn1[0])
+            p2 = get_turbine_coord(conn1[1])
+            p3 = get_turbine_coord(conn2[0])
+            p4 = get_turbine_coord(conn2[1])
+
+            if (
+                np.array_equal(p1, p3)
+                or np.array_equal(p1, p4)
+                or np.array_equal(p2, p3)
+                or np.array_equal(p2, p4)
+            ):
+                continue
+
+            if line_intersection(p1, p2, p3, p4):
+                crossings.append((i, j, p1, p2, p3, p4))
+
+    return crossings

pyproject.toml

@@ -12,6 +12,8 @@ dependencies = [
     "numpy>=2.4.0",
     "openpyxl>=3.1.5",
     "pandas>=2.3.3",
+    "pulp>=3.3.0",
+    "pyomo>=6.9.5",
     "pywebview>=6.1",
     "scikit-learn>=1.8.0",
     "scipy>=1.16.3",

test_cbc_solver.py

@@ -0,0 +1,146 @@
+"""
+Simple test to verify CBC solver functionality
+"""
+
+import pulp
+import sys
+import subprocess
+import os
+
+print("=== PuLP and CBC Solver Test ===")
+print(f"Python version: {sys.version}")
+print(f"PuLP version: {pulp.__version__}")
+
+# Test 1: Check PuLP installation
+print("\n1. Checking PuLP installation...")
+try:
+    from pulp import LpProblem, LpVariable, LpMinimize, LpMaximize, lpSum, value
+
+    print("[OK] PuLP imported successfully")
+except ImportError as e:
+    print(f"[FAIL] PuLP import failed: {e}")
+    sys.exit(1)
+
+# Test 2: Check CBC solver file existence
+print("\n2. Checking CBC solver file...")
+solver_dir = os.path.join(
+    os.path.dirname(pulp.__file__), "apis", "..", "solverdir", "cbc", "win", "i64"
+)
+solver_path = os.path.join(solver_dir, "cbc.exe")
+
+print(f"Looking for CBC at: {solver_path}")
+if os.path.exists(solver_path):
+    print(f"[OK] CBC solver file found")
+    file_size = os.path.getsize(solver_path)
+    print(f"  File size: {file_size:,} bytes ({file_size / 1024 / 1024:.2f} MB)")
+else:
+    print(f"[FAIL] CBC solver file not found")
+    print(f"  Checking directory contents:")
+    try:
+        parent_dir = os.path.dirname(solver_path)
+        if os.path.exists(parent_dir):
+            for item in os.listdir(parent_dir):
+                print(f"    - {item}")
+        else:
+            print(f"  Directory does not exist: {parent_dir}")
+    except Exception as e:
+        print(f"  Error listing directory: {e}")
+
+# Test 3: Try to run CBC solver directly
+print("\n3. Testing CBC solver execution...")
+if os.path.exists(solver_path):
+    try:
+        result = subprocess.run(
+            [solver_path, "-version"],
+            capture_output=True,
+            text=True,
+            timeout=10,
+            check=True,
+        )
+        print("[OK] CBC solver executed successfully")
+        print(f"  Output: {result.stdout[:200]}")
+    except subprocess.CalledProcessError as e:
+        print(f"[FAIL] CBC solver execution failed (exit code {e.returncode})")
+        print(f"  stdout: {e.stdout[:200]}")
+        print(f"  stderr: {e.stderr[:200]}")
+    except subprocess.TimeoutExpired:
+        print("[FAIL] CBC solver execution timed out")
+    except Exception as e:
+        print(f"[FAIL] CBC solver execution error: {e}")
+else:
+    print("[FAIL] Cannot test CBC execution - file not found")
+
+# Test 4: Solve a simple linear programming problem
+print("\n4. Testing simple LP problem...")
+try:
+    # Simple problem: minimize x + y subject to x + y >= 5, x >= 0, y >= 0
+    prob = LpProblem("Simple_LP_Test", LpMinimize)
+
+    x = LpVariable("x", lowBound=0, cat="Continuous")
+    y = LpVariable("y", lowBound=0, cat="Continuous")
+
+    prob += x + y  # Objective: minimize x + y
+    prob += x + y >= 5  # Constraint
+
+    print("  Created simple LP problem: minimize x + y subject to x + y >= 5")
+
+    # Try to solve with CBC
+    solver = pulp.PULP_CBC_CMD(msg=False, timeLimit=10)
+    print("  Attempting to solve with CBC...")
+
+    status = prob.solve(solver)
+
+    print(f"[OK] LP problem solved")
+    print(f"  Status: {pulp.LpStatus[prob.status]}")
+    print(f"  Objective value: {value(prob.objective)}")
+    print(f"  x = {value(x)}, y = {value(y)}")
+
+    if abs(value(prob.objective) - 5.0) < 0.01:
+        print("  [OK] Correct solution found!")
+    else:
+        print(f"  [FAIL] Unexpected solution (expected 5.0)")
+
+except Exception as e:
+    print(f"[FAIL] LP problem solving failed: {e}")
+    import traceback
+
+    traceback.print_exc()
+
+# Test 5: Solve a simple mixed integer programming problem
+print("\n5. Testing simple MIP problem...")
+try:
+    # Simple MIP: minimize x + y subject to x + y >= 5, x, y integers >= 0
+    prob = LpProblem("Simple_MIP_Test", LpMinimize)
+
+    x = LpVariable("x", lowBound=0, cat="Integer")
+    y = LpVariable("y", lowBound=0, cat="Integer")
+
+    prob += x + y  # Objective
+    prob += x + y >= 5  # Constraint
+
+    print(
+        "  Created simple MIP problem: minimize x + y subject to x + y >= 5, x,y integers"
+    )
+
+    solver = pulp.PULP_CBC_CMD(msg=False, timeLimit=10)
+    print("  Attempting to solve with CBC...")
+
+    status = prob.solve(solver)
+
+    print(f"[OK] MIP problem solved")
+    print(f"  Status: {pulp.LpStatus[prob.status]}")
+    print(f"  Objective value: {value(prob.objective)}")
+    print(f"  x = {value(x)}, y = {value(y)}")
+
+    if abs(value(prob.objective) - 5.0) < 0.01:
+        print("  [OK] Correct solution found!")
+    else:
+        print(f"  [FAIL] Unexpected solution (expected 5.0)")
+
+except Exception as e:
+    print(f"[FAIL] MIP problem solving failed: {e}")
+    import traceback
+
+    traceback.print_exc()
+
+print("\n=== Test Complete ===")

test_mip.py

@@ -0,0 +1,50 @@
+"""
+Test script to verify MIP functionality
+"""
+
+import numpy as np
+import pandas as pd
+from mip import design_with_mip
+
+# Create test data
+np.random.seed(42)
+n_turbines = 10
+turbines = pd.DataFrame(
+    {
+        "x": np.random.uniform(0, 2000, n_turbines),
+        "y": np.random.uniform(0, 2000, n_turbines),
+        "power": np.random.uniform(5, 10, n_turbines),
+    }
+)
+
+substation = np.array([1000, 1000])
+
+print("Test data created:")
+print(f"Number of turbines: {n_turbines}")
+print(f"Substation location: {substation}")
+print(f"Total power: {turbines['power'].sum():.2f} MW")
+
+# Test MIP function
+print("\nTesting MIP design...")
+try:
+    connections, turbines_with_clusters = design_with_mip(
+        turbines,
+        substation,
+        cable_specs=None,
+        voltage=66000,
+        power_factor=0.95,
+        system_params=None,
+        max_clusters=None,
+        time_limit=30,
+        evaluate_func=None,
+        total_invest_func=None,
+        get_max_capacity_func=None,
+    )
+    print(f"MIP test successful!")
+    print(f"Number of connections: {len(connections)}")
+    print(f"Clusters assigned: {turbines_with_clusters['cluster'].tolist()}")
+except Exception as e:
+    print(f"MIP test failed with error: {e}")
+    import traceback
+
+    traceback.print_exc()

uv.lock

@@ -1243,6 +1243,15 @@ wheels = [
     { url = "https://mirrors.pku.edu.cn/pypi/web/packages/fc/f5/68334c015eed9b5cff77814258717dec591ded209ab5b6fb70e2ae873d1d/pillow-12.1.0-cp314-cp314t-win_arm64.whl", hash = "sha256:f61333d817698bdcdd0f9d7793e365ac3d2a21c1f1eb02b32ad6aefb8d8ea831" },
 ]
 
+[[package]]
+name = "ply"
+version = "3.11"
+source = { registry = "https://mirrors.pku.edu.cn/pypi/web/simple" }
+sdist = { url = "https://mirrors.pku.edu.cn/pypi/web/packages/e5/69/882ee5c9d017149285cab114ebeab373308ef0f874fcdac9beb90e0ac4da/ply-3.11.tar.gz", hash = "sha256:00c7c1aaa88358b9c765b6d3000c6eec0ba42abca5351b095321aef446081da3" }
+wheels = [
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/a3/58/35da89ee790598a0700ea49b2a66594140f44dec458c07e8e3d4979137fc/ply-3.11-py2.py3-none-any.whl", hash = "sha256:096f9b8350b65ebd2fd1346b12452efe5b9607f7482813ffca50c22722a807ce" },
+]
+
 [[package]]
 name = "propcache"
 version = "0.4.1"
@@ -1333,6 +1342,15 @@ version = "0.1.0"
 source = { registry = "https://mirrors.pku.edu.cn/pypi/web/simple" }
 sdist = { url = "https://mirrors.pku.edu.cn/pypi/web/packages/f2/cf/77d3e19b7fabd03895caca7857ef51e4c409e0ca6b37ee6e9f7daa50b642/proxy_tools-0.1.0.tar.gz", hash = "sha256:ccb3751f529c047e2d8a58440d86b205303cf0fe8146f784d1cbcd94f0a28010" }
 
+[[package]]
+name = "pulp"
+version = "3.3.0"
+source = { registry = "https://mirrors.pku.edu.cn/pypi/web/simple" }
+sdist = { url = "https://mirrors.pku.edu.cn/pypi/web/packages/16/1c/d880b739b841a8aa81143091c9bdda5e72e226a660aa13178cb312d4b27f/pulp-3.3.0.tar.gz", hash = "sha256:7eb99b9ce7beeb8bbb7ea9d1c919f02f003ab7867e0d1e322f2f2c26dd31c8ba" }
+wheels = [
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/99/6c/64cafaceea3f99927e84b38a362ec6a8f24f33061c90bda77dfe1cd4c3c6/pulp-3.3.0-py3-none-any.whl", hash = "sha256:dd6ad2d63f196d1254eddf9dcff5cd224912c1f046120cb7c143c5b0eda63fae" },
+]
+
 [[package]]
 name = "pycparser"
 version = "2.23"
@@ -1571,6 +1589,34 @@ wheels = [
     { url = "https://mirrors.pku.edu.cn/pypi/web/packages/2d/86/637cda4983dc0936b73a385f3906256953ac434537b812814cb0b6d231a2/pyobjc_framework_webkit-12.1-cp314-cp314t-macosx_10_15_universal2.whl", hash = "sha256:1aaa3bf12c7b68e1a36c0b294d2728e06f2cc220775e6dc4541d5046290e4dc8" },
 ]
 
+[[package]]
+name = "pyomo"
+version = "6.9.5"
+source = { registry = "https://mirrors.pku.edu.cn/pypi/web/simple" }
+dependencies = [
+    { name = "ply" },
+]
+sdist = { url = "https://mirrors.pku.edu.cn/pypi/web/packages/87/d8/f32e0dcacc8219694709200d4402c86a6e28d3af50380a5ccf7f7e15ffae/pyomo-6.9.5.tar.gz", hash = "sha256:0734020fcd5cc03ee200fd3f79d143fbfc14e6be116e0d16bab79f3f89609879" }
+wheels = [
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/f8/63/5f163b231a924ba7a5f6c58466c751f70be88568fa446524b6e806c98e4b/pyomo-6.9.5-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:549ee4226cab6e2ff6efe5b3b9891ce1dfd866d38a024715315ea850fa1bf0ec" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/2d/bf/0cebcfce70be04d6d7aa19fbcbdeecdd5843caac617424f34ab3feb8e96e/pyomo-6.9.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b382cc8c3728199c8332024d64eed8622dabb3f8aebe5874c86a036489064f7a" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/14/27/967545514a2d0f4ca5ac6b595661cb0927cdcd10c3bb2832c5aa0ee15990/pyomo-6.9.5-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:43c6e425ca5231b530cd23460e371b7ca9119224dd57237c34580e15f31e4d72" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/85/fe/691e5eb26f58ee4a072add6cc484756d9e3c367901ec6701d2c6789b394d/pyomo-6.9.5-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a1923c358e1e8009a05ada911fc72e615c9e2ce6988f0979ec1ecc75880ee1f7" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/c7/b3/ae47340790f2f1f92f76b176acf475890717f0cb7def073e504b9857a057/pyomo-6.9.5-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:694262dc2eb53ca1ab245261f432a5ed1ec30cf3e651b5a6a1c276bc2dd81076" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/29/e9/7f782864afd28a9eb53057c9d046541be6535b2da35e11c2bcb80839c6bd/pyomo-6.9.5-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1f99ce91f2710d60b380a3a519288282d2183c44e1d66c131909313a3b63e7a2" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/cd/4d/9ca17a602e31a1c3f3148c455a5739fcbe23c102b80a12ec3e6d3bf5e847/pyomo-6.9.5-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d22f99e0ba8e2fb7d0e806bf630b8ce9b0a41d777c51f22711adbcb905f7486e" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/44/2e/78c3ac876791b59c836338b73dc49317b01cef574b01af061999a04a064a/pyomo-6.9.5-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d5953e490b9e9ea42d28804dd0358a9d3ef82560022c2b538e70a638790bc392" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/3c/27/3eb3db8e9ed6a01dee63219389aec761d5cc29b6dc5015b32f826f2a9225/pyomo-6.9.5-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:058eddde05b4354307975f1ecd25cfda9f8a282ad2e3b4f168ff8fee3c3623a1" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/9a/31/7f4750fc9bb0ec18a9534549e4c80ea63f1267aa828d495a48bbf0018f49/pyomo-6.9.5-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:105a073c47a2d2d6e74e48ed6fc82c6f6d19027488d5003aabb7ed5d10271483" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/f8/67/639d0006eddab30cf415b0154763ccc51f3c15b934e866eb4fb07bc2b6ed/pyomo-6.9.5-cp314-cp314-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f2c636c2c640b33dde3b119f6f0941a1bbde39397c392dba55351b0438d8600f" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/67/ef/023b74b8f161f15a51febdd160354f1e3fd7e1475abbe5ccfb3d7588cf1f/pyomo-6.9.5-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e02813b4021eeed7214a1ca5d7daecbdc78d3db7059962553a57fd138d747c22" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/a0/ca/edab1b532fd5e2d146d0cb96836eb5ae387b8a5bd255213e306793f6168e/pyomo-6.9.5-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:83789ce89271da31e0ff5bbef692af1621ab1747798183a5603b6577b7074277" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/a9/3c/2745386f57030bc60b626adba002b68db3f9538d5b52900f48026a4a17d7/pyomo-6.9.5-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:1f449aaceac5078daaecc21d19b96a15529f9ac8aa90f6472e8811cc07112ecc" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/f1/93/2058af0890b13f7e1a26e4925ff8d681c23d9cbdc2ecc9db17c744941617/pyomo-6.9.5-cp314-cp314t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f94d03f122fcf04a769c28ad48c423cd7b6d3d2c40da20bc8ea1a41bb20d0c36" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/de/30/c808931fc034851a16d3f8360d045b087ac743ea97bfe96cdb4b1df47c21/pyomo-6.9.5-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:96ff300e96cdab75e2e6983c99e3a61eaff2a6d0f5ed83acd939e74e361de537" },
+    { url = "https://mirrors.pku.edu.cn/pypi/web/packages/68/29/394967f7df51788cbdf1b4aedfb7c5a3a62e11b85b4c9d806b86cc576be4/pyomo-6.9.5-py3-none-any.whl", hash = "sha256:60326f7d3143ee7d0f5c5c4a3cbf871b53e08cc6c2b0c9e6d25568880233472f" },
+]
+
 [[package]]
 name = "pyparsing"
 version = "3.3.1"
@@ -2106,6 +2152,8 @@ dependencies = [
     { name = "numpy" },
     { name = "openpyxl" },
     { name = "pandas" },
+    { name = "pulp" },
+    { name = "pyomo" },
     { name = "pywebview" },
     { name = "scikit-learn" },
     { name = "scipy" },
@@ -2125,6 +2173,8 @@ requires-dist = [
     { name = "numpy", specifier = ">=2.4.0" },
     { name = "openpyxl", specifier = ">=3.1.5" },
     { name = "pandas", specifier = ">=2.3.3" },
+    { name = "pulp", specifier = ">=3.3.0" },
+    { name = "pyomo", specifier = ">=6.9.5" },
     { name = "pywebview", specifier = ">=6.1" },
     { name = "scikit-learn", specifier = ">=1.8.0" },
     { name = "scipy", specifier = ">=1.16.3" },

win32_helper.py

@@ -0,0 +1,232 @@
+import ctypes
+import ctypes.wintypes
+import os
+
+def show_save_dialog_win32():
+    """
+    使用 ctypes 直接调用 Windows API (GetSaveFileNameW)
+    不需要子进程，可以在线程中运行 (run.io_bound)
+    """
+    try:
+        # 定义 OPENFILENAME 结构体
+        class OPENFILENAME(ctypes.Structure):
+            _fields_ = [
+                ("lStructSize", ctypes.wintypes.DWORD),
+                ("hwndOwner", ctypes.wintypes.HWND),
+                ("hInstance", ctypes.wintypes.HINSTANCE),
+                ("lpstrFilter", ctypes.wintypes.LPCWSTR),
+                ("lpstrCustomFilter", ctypes.wintypes.LPWSTR),
+                ("nMaxCustFilter", ctypes.wintypes.DWORD),
+                ("nFilterIndex", ctypes.wintypes.DWORD),
+                ("lpstrFile", ctypes.wintypes.LPWSTR),
+                ("nMaxFile", ctypes.wintypes.DWORD),
+                ("lpstrFileTitle", ctypes.wintypes.LPWSTR),
+                ("nMaxFileTitle", ctypes.wintypes.DWORD),
+                ("lpstrInitialDir", ctypes.wintypes.LPCWSTR),
+                ("lpstrTitle", ctypes.wintypes.LPCWSTR),
+                ("Flags", ctypes.wintypes.DWORD),
+                ("nFileOffset", ctypes.wintypes.WORD),
+                ("nFileExtension", ctypes.wintypes.WORD),
+                ("lpstrDefExt", ctypes.wintypes.LPCWSTR),
+                ("lCustData", ctypes.wintypes.LPARAM),
+                ("lpfnHook", ctypes.wintypes.LPVOID),
+                ("lpTemplateName", ctypes.wintypes.LPCWSTR),
+                # 还有更多字段，但这通常足够了
+                # ("pvReserved", ctypes.wintypes.LPVOID),
+                # ("dwReserved", ctypes.wintypes.DWORD),
+                # ("FlagsEx", ctypes.wintypes.DWORD),
+            ]
+
+        # 准备缓冲区
+        filename_buffer = ctypes.create_unicode_buffer(260) # MAX_PATH
+        # 设置初始文件名
+        filename_buffer.value = "win32_save.xlsx"
+        
+        # 准备过滤器 (用 \0 分隔)
+        # 格式: "描述\0模式\0描述\0模式\0\0"
+        filter_str = "Excel Files (*.xlsx)\0*.xlsx\0All Files (*.*)\0*.*\0\0"
+        
+        ofn = OPENFILENAME()
+        ofn.lStructSize = ctypes.sizeof(OPENFILENAME)
+        ofn.hwndOwner = 0 # NULL
+        ofn.lpstrFilter = filter_str
+        ofn.lpstrFile = ctypes.cast(filename_buffer, ctypes.wintypes.LPWSTR)
+        ofn.nMaxFile = 260
+        ofn.lpstrDefExt = "xlsx"
+        ofn.lpstrTitle = "保存文件 (Win32 API)"
+        # OFN_OVERWRITEPROMPT | OFN_PATHMUSTEXIST | OFN_NOCHANGEDIR
+        ofn.Flags = 0x00000002 | 0x00000800 | 0x00000008 
+        
+        comdlg32 = ctypes.windll.comdlg32
+        
+        # 调用 API
+        # GetSaveFileNameW 返回非零值表示成功
+        if comdlg32.GetSaveFileNameW(ctypes.byref(ofn)):
+            return filename_buffer.value
+        else:
+            return None
+            
+    except Exception as e:
+        print(f"Win32 API Error: {e}")
+        return None
+
+
+def show_save_dialog_com():
+    """
+    使用 COM 接口 IFileSaveDialog (Windows Vista+)
+    提供更现代化的文件保存对话框，支持更多功能
+    """
+    try:
+        import ctypes
+        import ctypes.wintypes
+        import uuid
+
+        # 定义必要的常量
+        CLSCTX_INPROC_SERVER = 1
+        S_OK = 0
+        FOS_OVERWRITEPROMPT = 0x00000002
+        FOS_PATHMUSTEXIST = 0x00000800
+        FOS_NOCHANGEDIR = 0x00000008
+        SIGDN_FILESYSPATH = 0x80058000
+
+        # IFileSaveDialog 的 CLSID 和 IID
+        CLSID_FileSaveDialog = uuid.UUID("{C0B4E2F3-BA21-4773-8DBA-335EC946EB8B}")
+        IID_IFileSaveDialog = uuid.UUID("{84bccd23-5fde-4cdb-aea4-af64b83d78ab}")
+        IID_IShellItem = uuid.UUID("{43826d1e-e718-42ee-bc55-a1e261c37bfe}")
+
+        # 加载 ole32.dll
+        ole32 = ctypes.windll.ole32
+
+        # CoInitialize
+        ole32.CoInitialize(None)
+
+        # CoCreateInstance
+        p_dialog = ctypes.c_void_p()
+        hr = ole32.CoCreateInstance(
+            ctypes.byref(CLSID_FileSaveDialog),
+            None,
+            CLSCTX_INPROC_SERVER,
+            ctypes.byref(IID_IFileSaveDialog),
+            ctypes.byref(p_dialog)
+        )
+
+        if hr != S_OK:
+            print(f"CoCreateInstance failed: {hr}")
+            return None
+
+        # 定义 IFileSaveDialog 的 vtable 方法
+        # 我们只需要调用 Show, GetResult, SetOptions, SetFileName, SetDefaultExtension, SetFileTypeIndex
+        # 这些方法在 IFileOpenDialog 基类中定义
+
+        # SetOptions
+        class IFileSaveDialogVtbl(ctypes.Structure):
+            _fields_ = [
+                ("QueryInterface", ctypes.c_void_p),
+                ("AddRef", ctypes.c_void_p),
+                ("Release", ctypes.c_void_p),
+                # IModalWindow
+                ("Show", ctypes.c_void_p),
+                # IFileDialog
+                ("SetFileTypes", ctypes.c_void_p),
+                ("SetFileTypeIndex", ctypes.c_void_p),
+                ("GetFileTypeIndex", ctypes.c_void_p),
+                ("Advise", ctypes.c_void_p),
+                ("Unadvise", ctypes.c_void_p),
+                ("SetOptions", ctypes.CFUNCTYPE(ctypes.c_long, ctypes.c_void_p, ctypes.c_ulong)),
+                ("GetOptions", ctypes.c_void_p),
+                ("SetDefaultFolder", ctypes.c_void_p),
+                ("SetFolder", ctypes.c_void_p),
+                ("GetFolder", ctypes.c_void_p),
+                ("GetCurrentSelection", ctypes.c_void_p),
+                ("SetFileName", ctypes.CFUNCTYPE(ctypes.c_long, ctypes.c_void_p, ctypes.c_wchar_p)),
+                ("GetFileName", ctypes.c_void_p),
+                ("SetTitle", ctypes.c_void_p),
+                ("SetOkButtonLabel", ctypes.c_void_p),
+                ("SetFileNameLabel", ctypes.c_void_p),
+                ("GetResult", ctypes.CFUNCTYPE(ctypes.c_long, ctypes.c_void_p, ctypes.POINTER(ctypes.c_void_p))),
+                ("AddPlace", ctypes.c_void_p),
+                ("SetDefaultExtension", ctypes.CFUNCTYPE(ctypes.c_long, ctypes.c_void_p, ctypes.c_wchar_p)),
+                ("Close", ctypes.c_void_p),
+                ("SetClientGuid", ctypes.c_void_p),
+                ("ClearClientData", ctypes.c_void_p),
+                ("SetFilter", ctypes.c_void_p),
+            ]
+
+        # 获取 vtable
+        vtable = ctypes.cast(p_dialog, ctypes.POINTER(ctypes.POINTER(IFileSaveDialogVtbl))).contents.contents
+
+        # 调用 SetOptions
+        hr = vtable.SetOptions(p_dialog, FOS_OVERWRITEPROMPT | FOS_PATHMUSTEXIST | FOS_NOCHANGEDIR)
+        if hr != S_OK:
+            print(f"SetOptions failed: {hr}")
+            return None
+
+        # 调用 SetFileName
+        hr = vtable.SetFileName(p_dialog, "com_save.xlsx")
+        if hr != S_OK:
+            print(f"SetFileName failed: {hr}")
+            return None
+
+        # 调用 SetDefaultExtension
+        hr = vtable.SetDefaultExtension(p_dialog, "xlsx")
+        if hr != S_OK:
+            print(f"SetDefaultExtension failed: {hr}")
+            return None
+
+        # 调用 SetFileTypeIndex
+        hr = vtable.SetFileTypeIndex(p_dialog, 1)
+        if hr != S_OK:
+            print(f"SetFileTypeIndex failed: {hr}")
+            return None
+
+        # 调用 Show
+        hr = vtable.Show(p_dialog, 0)  # 0 表示没有父窗口
+        if hr != S_OK:
+            # 用户取消
+            return None
+
+        # 调用 GetResult
+        p_result = ctypes.c_void_p()
+        hr = vtable.GetResult(p_dialog, ctypes.byref(p_result))
+        if hr != S_OK:
+            print(f"GetResult failed: {hr}")
+            return None
+
+        # 定义 IShellItem 接口
+        class IShellItemVtbl(ctypes.Structure):
+            _fields_ = [
+                ("QueryInterface", ctypes.c_void_p),
+                ("AddRef", ctypes.c_void_p),
+                ("Release", ctypes.c_void_p),
+                ("BindToHandler", ctypes.c_void_p),
+                ("GetParent", ctypes.c_void_p),
+                ("GetDisplayName", ctypes.CFUNCTYPE(ctypes.c_long, ctypes.c_void_p, ctypes.c_ulong, ctypes.POINTER(ctypes.c_wchar_p))),
+                ("GetAttributes", ctypes.c_void_p),
+                ("Compare", ctypes.c_void_p),
+            ]
+
+        # 获取 IShellItem 的 vtable
+        result_vtable = ctypes.cast(p_result, ctypes.POINTER(ctypes.POINTER(IShellItemVtbl))).contents.contents
+
+        # 调用 GetDisplayName
+        p_display_name = ctypes.c_wchar_p()
+        hr = result_vtable.GetDisplayName(p_result, SIGDN_FILESYSPATH, ctypes.byref(p_display_name))
+        if hr != S_OK:
+            print(f"GetDisplayName failed: {hr}")
+            return None
+
+        filepath = p_display_name.value
+
+        # 清理
+        ole32.CoUninitialize()
+
+        return filepath
+
+    except ImportError as e:
+        print(f"COM Error: {e}")
+        return None
+    except Exception as e:
+        print(f"COM Error: {e}")
+        import traceback
+        traceback.print_exc()
+        return None