含仿真录像，基于BBKH磷虾种群迁移优化算法的目标优化matlab仿真

clc; clear; close all; warning off; addpath(genpath(pwd)); rng('default'); % Problem Statement Npar = 3; VarLow=[-5.12 -5.12 -5.12]; VarHigh = [5.12 5.12 5.12]; % parameters NP=100; %number of krills MaxIter=100; %number of iterations Vf=0.2; %foraging velocity Dmax=0.005; %max diffusion Nmax=0.01; pmod=0.5; wf = 0.3; %inertia for foraging wn= 0.3; %inertia for movement mu=0.3; XBest = [0.5 0.5 0.5]; XBestFit = fitnessFunc(XBest); GB=XBestFit; t = cputime; %Initialization only for memory allocation Krill=repmat(struct('Position',zeros(1,Npar),'Velocity',zeros(1,Npar)),NP,1); %Random Population for ii = 1:NP Krill(ii).Position = rand(1,Npar).* (VarHigh - VarLow) + VarLow; Krill(ii).N=rand(1,Npar); Krill(ii).F=rand(1,Npar); Krill(ii).Fit = fitnessFunc(Krill(ii).Position); end %main loop for kk = 1:MaxIter rng(kk); %Sorting the population according to their fitness [~,sortind]=sort([Krill.Fit]); Krill = Krill(sortind); %store the best krill if Krill(1).Fit<XBestFit XBest=Krill(1).Position; XBestFit=Krill(1).Fit; end for ii=1:NP %movement Krill(ii).N=Nmax+wn*(Krill(ii).N); %foraging beta=XBest-Krill(ii).Position; Krill(ii).F=Vf*beta+ wf*(Krill(ii).F); %diffusion D=Dmax*rand(1,Npar); %new position Krill(ii).Position=Krill(ii).Position+Krill(ii).N+D+Krill(ii).F; %Krill Migration operator if rand<pmod for jj=1:Npar j=randperm(NP,1); if rand<mu Krill(ii).Position(jj)=Krill(j).Position(jj); end end end %limit within boundaries Krill(ii).Positon=limiter(Krill(ii).Position,VarLow,VarHigh); %find the fitness value Krill(ii).Fit =fitnessFunc(Krill(ii).Position); end % store the best value in each iteration GB=[GB XBestFit]; end t1=cputime; fprintf('The time taken is %3.2f seconds \n',t1-t); fprintf('The best value is :'); XBest XBestFit figure(1) plot(0:MaxIter,GB, 'linewidth',1.2); title('Convergence'); xlabel('Iterations'); ylabel('Objective Function (Cost)'); grid('on')