diff --git a/main.m b/main.m
index 1ff6f70..065f62c 100644
--- a/main.m
+++ b/main.m
@@ -3,10 +3,12 @@ clear
 close all
 %先形成初始点
 center=[1,1,1,1,1;10,10,10,10,10;100,100,100,100,100;1000,1000,1000,1000,1000];
-center=[1;10;100;1000];
-dataN=50;% 生成多少个数据
-Dim=1;
+% center=[1;10;100;1000];
+dataN=100;% 生成多少个数据
+Dim=5;
+clusterN=5;
 data=zeros(Dim,dataN);
+% data=[11,101,1001,1,2,3];
 for I=1:dataN
     i=round(1+(4-1)*rand());
     data(:,I)=center(i)*( -1+(1+1)*rand(Dim,1));
@@ -15,7 +17,7 @@ end
 
 SetS=[1;];
 
-for clusterI=1:3
+for clusterI=1:clusterN-1
     maxG=-100*ones(dataN,1);
     for cluster=1:dataN
         if sum(ismember(cluster,SetS))>0
@@ -48,4 +50,71 @@ for clusterI=1:3
     end
     maxGInd=find(maxG==max(maxG));
     SetS=[SetS;maxGInd(1)];
+end
+SetS
+%% 进入SWAP部分
+% SetS=[1;2;3];
+USetS=setxor(1:dataN,SetS);
+
+while 1
+    minKjih=1e20;
+    for I=1:length(SetS)
+        for H=1:length(USetS)
+            %交换两个集合的元素
+            cadSetS=SetS;
+            cadUSetS=USetS;
+            swap=cadSetS(I);
+            cadSetS(I)=cadUSetS(H);
+            cadUSetS(H)=swap;
+            sumKjih=0;
+            for D=1:length(cadUSetS)
+                J=cadUSetS(D);
+                d=data(:,J);
+                if J==cadSetS(I)
+                    continue
+                end
+                minD=1e20;
+                min2D=minD;
+                for G=1:length(SetS)%between j and the closest object in S.
+                    distance=sum((d-data(:,SetS(G))).^2).^.5;
+                    if distance<minD
+                        minD=distance;
+                    else
+                        if distance<min2D
+                            min2D=distance;
+                        end
+                    end
+                    
+                end
+                distanceIJ=sum((d-data(:,cadUSetS(H))).^2).^.5;%S(I)已经等于U(H)
+                distanceHJ=sum((d-data(:,cadSetS(I))).^2).^.5;
+                if distanceIJ>minD
+                    Kjih=min([distanceHJ-minD,0]);
+                end
+                if distanceIJ<minD
+                    fprintf('Input must be a string\n')
+                end
+                if abs(distanceIJ-minD)<1e-5
+                    Kjih=min([distanceHJ,min2D])-minD;
+                end
+                sumKjih=sumKjih+Kjih;
+            end
+            if sumKjih<minKjih
+                minKjih=sumKjih;
+                minSetS=cadSetS;
+                minUSetS=cadUSetS;
+            end
+        end
+    end
+    if minKjih<0
+        minKjih
+        SetS=minSetS;
+        USetS=minUSetS;
+        SetS
+    else
+        minKjih
+        SetS
+        fprintf('clustering is done.\n')
+        break;
+    end
 end
\ No newline at end of file