Add MIP module for collector layout optimization

main.py

@@ -15,6 +15,11 @@ from sklearn.cluster import KMeans
 from esau_williams import design_with_esau_williams
 from ga import design_with_ga
 
+try:
+    from mip import design_with_mip
+except ImportError:
+    design_with_mip = None
+
 # 设置matplotlib支持中文显示
 plt.rcParams["font.sans-serif"] = ["Microsoft YaHei", "SimHei", "Arial"]
 plt.rcParams["axes.unicode_minus"] = False
@@ -1399,6 +1404,7 @@ def compare_design_methods(
     interactive=True,
     plot_results=True,
     use_ga=False,
+    use_mip=False,
 ):
     """
     比较MST和三种电缆方案下的K-means设计方法
@@ -1709,6 +1715,49 @@ def compare_design_methods(
                 f"  [GA] Cost: ¥{eval_ga['total_cost']:,.2f} | Loss: {eval_ga['total_loss']:.2f} kW | Circuits: {n_circuits_ga}"
             )
 
+        if use_mip and design_with_mip:
+            # --- Run 5: Mixed Integer Programming ---
+            mip_name = f"{name} (MIP)"
+            conns_mip, turbines_mip = design_with_mip(
+                turbines.copy(),
+                substation,
+                current_specs,
+                voltage,
+                power_factor,
+                system_params,
+                evaluate_func=evaluate_design,
+                total_invest_func=total_investment,
+                get_max_capacity_func=get_max_cable_capacity_mw,
+            )
+            eval_mip = evaluate_design(
+                turbines,
+                conns_mip,
+                substation,
+                cable_specs=current_specs,
+                is_offshore=is_offshore,
+                method_name=mip_name,
+                voltage=voltage,
+                power_factor=power_factor,
+            )
+            n_circuits_mip = sum(
+                1
+                for d in eval_mip["details"]
+                if d["source"] == "substation" or d["target"] == "substation"
+            )
+            comparison_results.append(
+                {
+                    "name": mip_name,
+                    "cost": eval_mip["total_cost"],
+                    "loss": eval_mip["total_loss"],
+                    "eval": eval_mip,
+                    "turbines": turbines_mip,
+                    "specs": current_specs,
+                }
+            )
+            print(
+                f"  [MIP] Cost: ¥{eval_mip['total_cost']:,.2f} | Loss: {eval_mip['total_loss']:.2f} kW | Circuits: {n_circuits_mip}"
+            )
+
         # 记录最佳
         if eval_rot["total_cost"] < best_cost:
             best_cost = eval_rot["total_cost"]