matlab遗传算法求解车间调度问题分析及实现源码

clc;clear
%% 下载数据
% 加工数据包括加工时间，加工机器，机器数，各机器权重，工件数，各工件对应的工序数
load data operation_time operation_machine num_machine machine_weight num_job num_op

%% 基本参数
MAXGEN = 200;               % 最大迭代次数
Ps = 0.8;                   % 选择率
Pc = 0.7;                   % 交叉率
Pm = 0.3;                   % 变异率
sizepop = 200;              % 个体数目
e = 0.5;                    % 目标值权重
trace = zeros(2,MAXGEN);

%% ===========================种群初始化============================
total_op_num=sum(num_op);
chroms=initialization(num_op,num_job,total_op_num,sizepop,operation_machine,operation_time);
[Z,~,~]=fitness(chroms,num_machine,e,num_job,num_op);

%% ============================迭代过程=============================
for gen=1:MAXGEN
    fprintf('当前迭代次数：'),disp(gen)
    % 轮盘赌选择
    chroms_new=selection(chroms,Z,Ps);
    % 交叉操作
    chroms_new=crossover(chroms_new,Pc,total_op_num,num_job,num_op);
    % 变异操作
    chroms_new=mutation(chroms_new,total_op_num,Pm,num_machine,e,num_job,num_op,operation_machine,operation_time);
    % 计算选择交叉变异后个体的适应度
    [Z_new,~,~]=fitness(chroms_new,num_machine,e,num_job,num_op);
    % 根据适应度在原种群和遗传操作后的种群中选出sizepop个更优个体
    [chroms,Z,chrom_best]=update_chroms(chroms,chroms_new,Z,Z_new,sizepop);
    % 记录每代的最优适应度与平均适应度
    trace(1, gen)=Z(1);       
    trace(2, gen)=mean(Z);  
    % 更新全局最优适应度
    if gen==1 || MinVal>trace(1,gen)
        MinVal=trace(1,gen);
function [Z,machine_weight,pvals] = fitness(chroms,num_machine,e,num_job,num_op)
sizepop=size(chroms,1);
pvals=cell(1,sizepop);
Z1=zeros(1,sizepop);
Z2=Z1;
total_op_num=sum(num_op);  % 总工序数
for k=1:sizepop
    chrom=chroms(k,:);
    machine=zeros(1,num_machine);  % 记录各机器变化时间
    job=zeros(1,num_job);  % 记录各工件变化时间
    machine_time=zeros(1,num_machine);  % 计算各机器的实际加工时间
    pval=zeros(2,total_op_num);  % 记录各工序开始和结束时间
    for i=1:total_op_num
        % 机器时间大于工件时间
        if machine(chrom(total_op_num+i))>=job(chrom(i))
            pval(1,i)=machine(chrom(total_op_num+i));  % 记录工件开始时间
            machine(chrom(total_op_num+i))=machine(chrom(total_op_num+i))+chrom(total_op_num*2+i);
            job(chrom(i))=machine(chrom(total_op_num+i));
            pval(2,i)=machine(chrom(total_op_num+i));  % 记录工件结束时间
            % 机器时间小于工件时间
        else
            pval(1,i)=job(chrom(i));
            job(chrom(i))=job(chrom(i))+chrom(total_op_num*2+i);
            machine(chrom(total_op_num+i))=job(chrom(i));
            pval(2,i)=job(chrom(i));
        end
        machine_time(chrom(total_op_num+i))=machine_time(chrom(total_op_num+i))+chrom(total_op_num*2+i);
    end
    Z1(k)=max(machine);  % 最大机器时间值，对应makespan
    % machine_weight=machine_time/sum(machine_time);  % 计算各机器的负荷
    machine_weight=machine_time;
    Z2(k)=max(machine_weight)-min(machine_weight);
    pvals{k}=pval;
end
% min_makespan=min(Z1);%所有染色体的makespan最优值
% max_makespan=max(Z1);
% min_weight=min(Z2);%负载最优值
% max_weight=max(Z2);
% Z=e*((Z1-min_makespan)./(max_makespan-min_makespan))+(1-e)*((Z2-min_weight)./(max_weight-min_weight));%计算适应度
Z=e*Z1+(1-e)*Z2;

function [ chroms_new] = crossover(chroms,Pc,total_op_num,num_job,num_op)
size_chrom=size(chroms,1);  % 染色体数
chroms_new=chroms;
%% 面向工序码的交叉操作
for i=1:2:size_chrom-1 
    if Pc>rand
        % 父代染色体
        parent1=chroms(i,:);
        parent2=chroms(i+1,:);
        Job=randperm(num_job);
        % 将工件随机分成两个集合
        J1=Job(1:round(num_job/2));
        J2=Job(length(J1)+1:end);
        % 子代染色体
        child1=parent1;
        child2=parent2;
        op_p1=[];
        op_p2=[];
        for j=1:length(J2)
            %找出父代中J2片段对应的位置
            op_p1=[op_p1,find(parent1(1:total_op_num)==J2(j))];
            op_p2=[op_p2,find(parent2(1:total_op_num)==J2(j))];
        end
        op_s1=sort(op_p1);
        op_s2=sort(op_p2);
        % 子代1交换J2片段的基因，机器码对应位置的基因，工时码对应位置的基因
        child1(op_s1)=parent2(op_s2);
        child1(total_op_num+op_s1)=parent2(total_op_num+op_s2);
        child1(total_op_num*2+op_s1)=parent2(total_op_num*2+op_s2);
        % 子代2同理
        child2(op_s2)=parent1(op_s1);
        child2(total_op_num+op_s2)=parent1(total_op_num+op_s1);
        child2(total_op_num*2+op_s2)=parent1(total_op_num*2+op_s1);
        chroms_new(i,:)=child1;
        chroms_new(i+1,:)=child2;
    end
end
%% 面向机器码的交叉操作
for k=1:2:size_chrom-1
    if Pc>rand
        parent1=chroms_new(k,:);
        parent2=chroms_new(k+1,:);
        child1=parent1;
        child2=parent2;
        % 随机产生与染色体长度相等的0,1序列
        rand0_1=randi([0,1],1,total_op_num);
        for n=1:num_job
            ind_0=find(rand0_1(num_op(n)*(n-1)+1:num_op(n)*n)==0);
            if ~isempty(ind_0)
                temp1=find(parent1(1:total_op_num)==n);
                temp2=find(parent2(1:total_op_num)==n);
                child1(total_op_num+temp1(ind_0))=parent2(total_op_num+temp2(ind_0));
                child2(total_op_num+temp2(ind_0))=parent1(total_op_num+temp1(ind_0));
                child1(total_op_num*2+temp1(ind_0))=parent2(total_op_num*2+temp2(ind_0));
                child2(total_op_num*2+temp2(ind_0))=parent1(total_op_num*2+temp1(ind_0));
            end
        end
        chroms_new(k,:)=child1;
        chroms_new(k+1,:)=child2;
    end
end
end