【优化算法】多目标水循环算法（MOWCA）【含Matlab源码 1433期】

原创

Matlab科研 2021-11-08 11:04:58 ©著作权

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二、部分源代码

clear all;
close all;
clc;

global Factual nvars

%% FON (Benchmark Multi-Objective Function)

nvars=8;                    % Number of design variables
objective_function=@FON;

LB=ones(1,nvars)*-2;
UB=ones(1,nvars)*2;

% --------- Optimal Pareto Front ----------------
X=[(-1/sqrt(8)):(0.0001/sqrt(8)):(1/sqrt(8))]';

Xactual=repmat(X,1,nvars);
for i=1:length(X)
    Factual(i,:)=objective_function(Xactual(i,:));
end

%% -------------------------- MOWCA ---------------------------------------
for k=1:1   % Numbver of independent runs
    
    [Non_Dominated_Solutions,Pareto_Front,Used_NFEs,Elapsed_Time]=MOWCA_Unconstrained(objective_function,LB,UB,nvars)
    
    GD=Generational_distance(Pareto_Front,Factual);                     % Generational Distance Metric
    RGD=Reverse_generational_distance(Pareto_Front,Factual);            % Reverse Generational Distance Metric
    S=metric_of_spacing(Pareto_Front);                                  % Metric of Spacing
    DELTA=Diversity_metric_delta(Pareto_Front,Factual);                 % Delta Metric
    MS=metric_of_maximum_spread(Pareto_Front,Factual);                  % Metric of Maximum Spread
    
    % ------- Plot the final results ---------
    plot(Pareto_Front(:,1),Pareto_Front(:,2),'ro','LineWidth',2,...
        'MarkerEdgeColor','k',...
        'MarkerFaceColor','k',...
        'MarkerSize',4);
    hold on
    plot(Factual(:,1),Factual(:,2),'Color','blue','LineWidth',2)
    legend('Obtained PF','Optimal PF');
    hold off
    
    fprintf('%d %20.15f %20.15f %20.15f %20.15f %20.15f\n',k,GD,RGD,S,DELTA,MS);
    
    GGD(k)=GD;
    RRGD(k)=RGD;
    SS(k)=S;
    DELTAA(k)=DELTA;
    MSS(k)=MS;
    
end

Min_GD=min(GGD)
Average_GD=mean(GGD)
Median_GD=median(GGD)
Max_GD=max(GGD)
SD_GD=std(GGD)

Min_RGD=min(RRGD)
Average_RGD=mean(RRGD)
Median_RGD=median(RRGD)
Max_RGD=max(RRGD)
SD_RGD=std(RRGD)

Min_S=min(SS)
Average_S=mean(SS)
Median_S=median(SS)
Max_S=max(SS)
SD_S=std(SS)

Min_DELTA=min(DELTAA)
Average_DELTA=mean(DELTAA)
Median_DELTA=median(DELTAA)
Max_DELTA=max(DELTAA)
SD_DELTA=std(DELTAA)

Min_MS=min(MSS)
Average_MS=mean(MSS)
Median_MS=median(MSS)
Max_MS=max(MSS)
SD_MS=std(MSS)