FT06_java_GA_

/* * To change this license header, choose License Headers in Project Properties. * To change this template file, choose Tools | Templates * and open the template in the editor. */ package FT06; import java.util.ArrayList; import java.util.Arrays; import java.util.Collections; /** * * @author Administrator */ public class FT06 { public static int Popsize=20; public double v=0.9;//退温速率 public double Pr=0.1; public static int n=6;//工件数量 public static int m=6;//机器数量 public int[][] J={{3,1,2,4,6,5},{2,3,5,6,1,4},{3,4,6,1,2,5},{2,1,3,4,5,6},{3,2,5,6,1,4},{2,4,6,1,5,3}};/* 机器矩阵*/ public static int[][] T={{3,10,9,5,3,10},{6,8,1,5,3,3},{1,5,5,5,9,1},{7,4,4,3,1,3},{6,10,7,8,5,4},{3,10,8,9,4,9}};/* 加工时间矩阵*/ public int[]t=new int[Popsize];//种群各染色体加工时间 public int []tBest=new int[1];//种群中最佳时间 public int []scheduling=new int[n*m];//种群最优调度编码 public int [][]parentpopulation;//父代种群 public int[][]childpopulation=new int[Popsize][n*m];//子代种群 public int Kindex=0;//子代行数 public int[]Best=new int[n*m+1]; public int[][]selectpopulation=new int[2*Popsize][n*m+1]; public int[][]Psize=new int[Popsize][n*m+1]; public int finalgeneration=100; public int[][]Finalbest=new int[finalgeneration][n*m+1]; public int [] Bianma(){ int k=0; int l; int o; int[][]x=new int[n][m]; int []s=new int [n*m]; do{ do{ l=(int)(Math.random()*6+1); o=J[l-1][0]; } while(o==0); s[k]=l; k=k+1; for(int i=0;i<J[0].length;i++){ if(i<J[0].length-1){ J[l-1][i]=J[l-1][i+1]; }else{ J[l-1][i]=0; } } } while(!Arrays.deepEquals(J,x)); return s; } public void shuaxin(){ int[][]J={{3,1,2,4,6,5},{2,3,5,6,1,4},{3,4,6,1,2,5},{2,1,3,4,5,6},{3,2,5,6,1,4},{2,4,6,1,5,3}}; this.J=J; } public int[][] population(){ shuaxin(); int[][]xx=new int[Popsize][n*m]; for(int i=0;i<Popsize;i++){ xx[i]=Bianma(); shuaxin(); } /*for (int k = 0; k < Popsize; k++) { for (int j = 0; j < n * m; j++) { System.out.print(xx[k][j]); } System.out.println(""); }*/ this.parentpopulation=xx; return xx; } public int[] decoding(int [][]Chromosome){ int []time=new int[Chromosome.length]; for(int i=0;i<Chromosome.length;i++){ int []k=new int[n]; int []Jmin=new int [n]; int [][]MT=new int[m][2*n+1]; int []y=new int[m];//控制机器加工次数索引 int[][]MJ=new int[m][n];//机器工件排列阵 for(int j=0;j<n*m;j++){ int Jindex=Chromosome[i][j]-1;//工件在矩阵中索引 int x=J[Jindex][k[Jindex]];//加工机器号 k[Jindex]=k[Jindex]+1; int Tp=T[x-1][Jindex]; y[x-1]=y[x-1]+2; for(int ii=0;ii<=y[x-1]-2;ii=ii+2){ if(Math.max(Jmin[Jindex],(MT[x-1][ii]))+Tp<=MT[x-1][ii+1]){ for(int kk=y[x-1];kk>ii+2;kk=kk-2){ MT[x-1][kk-1]=MT[x-1][kk-3]; MT[x-1][kk]=MT[x-1][kk-2]; MJ[x-1][kk/2-1]=MJ[x-1][kk/2-2]; } MJ[x-1][ii/2]=Jindex+1; MT[x-1][ii+1]=Math.max(Jmin[Jindex],(MT[x-1][ii])); MT[x-1][ii+2]=MT[x-1][ii+1]+Tp; Jmin[Jindex]=Math.max(Jmin[Jindex],(MT[x-1][ii]))+Tp;//刷新最早加工时间 break; }else {if(ii==y[x-1]-2){ MJ[x-1][y[x-1]/2-1]=Jindex+1; MT[x-1][y[x-1]-1]=Math.max(Jmin[Jindex],MT[x-1][y[x-1]-2]); MT[x-1][y[x-1]]=MT[x-1][y[x-1]-1]+Tp; Jmin[Jindex]=Math.max(Jmin[Jindex],MT[x-1][y[x-1]-2])+Tp; } } } } for(int o=0;o<m;o++){ for(int p=0;p<2*n+1;p++){ System.out.print(MT[o][p]+" "); } System.out.println(""); }//打印加工时间矩阵 /*System.out.println(""); for(int o=0;o<m;o++){ for(int p=0;p<n;p++){ System.out.print(MJ[o][p]+" "); } System.out.println(""); } System.out.println("");//打印加工工件排列阵*/ int[]tt=new int[m]; for(int z=0;z<m;z++){ tt[z]=MT[z][2*n]; } Arrays.sort(tt); time[i]=tt[m-1]; } int best=time[0]; for(int i=0;i<Chromosome.length;i++){ if(time[i]<=best){ best=time[i]; tBest[0]=time[i]; scheduling=Chromosome[i]; } } /*System.out.print(tBest[0]); System.out.println(""); for(int k=0;k<n*m;k++){ System.out.print(scheduling[k]); } System.out.println("");*/ this.t=time; return time; } public void cross(){ int x=(int)(Math.random()*Popsize); int[]select1=parentpopulation[x]; int[]select2=scheduling; int[] a = { 1, 2, 3, 4, 5, 6 }; ArrayList<Integer> list = new ArrayList<Integer>(); for (int i:a) { list.add(i); } int[]b=new int[list.size()]; Collections.shuffle(list); Integer []array=new Integer[list.size()]; list.toArray(array); for(int i=0;i<a.length;i++){ b[i]=array[i].intValue(); } int c=(int)(Math.random()*(a.length-1))+1; int[] sub1 = Arrays.copyOf(b, c);//将工件集合分成两个互补集合 int[] sub2 = Arrays.copyOfRange(b, c, b.length);//确保遗传算子合法性 /*for(int i=0;i<c;i++){ System.out.print(sub1[i]); } System.out.println(""); for(int i=0;i<b.length-c;i++){ System.out.print(sub2[i]); } System.out.println(""); System.out.print(c); System.out.println("");打印随机分成的子集*/ int g=0;//控制列寻找满足条件值 int gg=0; for(int i=0;i<n*m;i++){ for(int j=0;j<c;j++){ if(parentpopulation[x][i]==sub1[j]){ childpopulation[Kindex][g]=parentpopulation[x][i]; g=g+1; } if(scheduling[i]==sub1[j]){ childpopulation[Kindex+1][gg]=scheduling[i]; gg=gg+1; } } } for(int i=0;i<n*m;i++){ for(int j=0;j<b.length-c;j++){ if(scheduling[i]==sub2[j]){ childpopulation[Kindex][g]=scheduling[i]; g=g+1; } if(parentpopulation[x][i]==sub2[j]){ childpopulation[Kindex+1][gg]=parentpopulation[x][i]; gg=gg+1; } } } } public void freshbest(){ Best[0]=tBest[0]; for(int i=0;i<n*m;i++){ Best[i+1]=scheduling[i]; } int p[]; p=decoding(childpopulation); for(int i=0;i<childpopulation.length;i++){ System.out.println(p[i]); } if(tBest[0]<=Best[0]){ Best[0]=tBest[0];