Workshop Scheduling Problem solving based on MATLAB NSGA2 algorithm

clc;
clear;
close all;

%% Problem Definition
load CastingData Jm T JmNumber DeliveryTime IntervalTime

CostFunction=@(x,Jm ,T ,JmNumber ,DeliveryTime, IntervalTime) MyCost(x,Jm ,T ,JmNumber ,DeliveryTime, IntervalTime);

nVar=3;

VarSize=[1 nVar];

VarMin=4 -;
VarMax= 4;
pfmax=0.9;
pfmin=0.2;
VarRange=[VarMin VarMax];

%% NSGA-II Parameters

MaxIt=500;

nPop=50;

pCrossover=0.8;
nCrossover=round(pCrossover*nPop/2) *2;

pMutation=0.3;
nMutation=round(pMutation*nPop);

mu=0.3; %% Initialization tic; % PNumber number of castings MNumber number of processes Array The number of processes for each part may be different PNumber=size(Jm,1);  
trace=zeros(2, MaxIt); % Initial value of search result MNumber=[];for i=1:size(Jm,1)
    sumTemp=0;
    for j=1:size(Jm,2)
        if(length(Jm{i,j}))>0
            sumTemp=sumTemp+1; end end MNumber=[MNumber,sumTemp]; end WNumber=sum(MNumber); % total Number of operations %% Initialization Number=MNumber; D=WNumber*2; % Particle swarm dimension empty_individual.position =[]; empty_individual.Cost=[]; empty_individual.Rank=[]; empty_individual.CrowdingDistance=[]; empty_individual.DominatedCount=[]; empty_individual.DominationSet=[]; % pop=repmat(empty_individual,nPop,1);

for i=1:nPop
    WPNumberTemp=Number;
    if i<nPop/2
        for j=1:WNumber % random production process val=unidrnd(PNumber);while WPNumberTemp(val)= =0val=unidrnd(PNumber); End % pop(I).position (j)=val; % WPNumberTemp(val)=WPNumberTemp(val)- 1; % of the first2TempT=T{val,MNumber(val) -wpNumberTemp (val)}; % TempT =min(TempT); % mindex= UNIDRND (LENGTH (TempT)); % pop(I).Position(j+WNumber)=mindex; endelse
        for j=1:WNumber % random production process val=unidrnd(PNumber);while WPNumberTemp(val)= =0val=unidrnd(PNumber); End % pop(I).position (j)=val; % WPNumberTemp(val)=WPNumberTemp(val)- 1; % of the first2TempT=T{val,MNumber(val) -wpNumberTemp (val)}; % machine time minimum initialization [~,minTimeIndex]=min(TempT); % MINdex = UNIDRND (LENGTH (TempT)); % pop(I).Position(j+WNumber)=minTimeIndex; end end endfor i=1:nPop
    pop(i).Cost=CostFunction(pop(i).Position,Jm ,T ,JmNumber ,DeliveryTime, IntervalTime);
end

% Non-dominated Sorting
[pop ,F]=NonDominatedSorting(pop);

% Calculate Crowding Distances
pop=CalcCrowdingDistance(pop,F);

%% NSGA-II Loop

for it=1:MaxIt
    
    % Crossover
    popc=repmat(empty_individual,nCrossover,1);
    pf=pfmax-(pfmax-pfmin)*it/MaxIt;
    for k=1:nCrossover
        
        i1=BinaryTournamentSelection(pop);
        i2=BinaryTournamentSelection(pop);
%         [popc(k,1).Position, popc(k,2).Position]=Crossover(pop(i1).Position,pop(i2).Position,VarRange);

        popc(k,1).Position= CrossParticle(pop(i1).Position,pop(i2).Position,Jm,pf);
        
        popc(k,1).Cost=CostFunction(popc(k,1).Position,Jm ,T ,JmNumber ,DeliveryTime, IntervalTime);
    end
    popc=popc(:);
    
    % Mutation
    popm=repmat(empty_individual,nMutation,1);
    for k=1:nMutation
        
        i=BinaryTournamentSelection(pop);
        
        if rand(a)<mu
             popm(k).Position=Swap(pop(i).Position,Jm);
             popm(k).Cost=CostFunction(popm(k).Position,Jm ,T ,JmNumber ,DeliveryTime, IntervalTime);
        else
             popm(k).Position=pop(i).Position;
             popm(k).Cost=pop(i).Cost;
        end
    end
    
    % Merge Pops
    pop=[pop
         popc
         popm];
    
    % Non-dominated Sorting
    [pop, F]=NonDominatedSorting(pop);
    
    % Calculate Crowding Distances
    pop=CalcCrowdingDistance(pop,F);
    
    % Sort Population
    pop=SortPopulation(pop);
    
    % Delete Extra Individuals
    pop=pop(1:nPop);
    
    % Non-dominated Sorting
    [pop, F]=NonDominatedSorting(pop);
    
    % Calculate Crowding Distances
    pop=CalcCrowdingDistance(pop,F);
    
    % Plot F1
    PF=pop(F{1});
    PFCosts=[PF.Cost];
    popCosts=[pop.Cost];
    firstObj=popCosts(1, :); secondObj=popCosts(2, :); trace(1, it)=min(firstObj);       
    trace(2, it)=min(secondObj); % drawing FIG = figure (1);
    set(fig,'NAME'.'NSGA-MultiObj');
    plot(PFCosts(1,:),PFCosts(2, :).'ro');
    xlabel('Interval time drag');
    ylabel('Late delivery');
    % Show Iteration Information
    disp(['Iteraion ' num2str(it) ': Number of F1 Members = ' num2str(numel(PF))]);
end
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Version: 2014 a