matlab-(含教程)基于静磁细菌优化算法(MBO)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 MaxIter=100; %Maximum iteration N=50; %Initial population c1 = 20; c2 =0.003; mp =0.6; B = 1; % initialize a random value as best value XBest = rand(1,Npar).* (VarHigh - VarLow) + VarLow; XBestCost = fitnessFunc(XBest); GB = XBestCost; t=cputime; % Initialize of magnetotatic bacteria and memory X = zeros(N,Npar); F = zeros(N, 1); Fnorm = F; for ii=1:N % initialize with a random solution X(ii,:)=rand(1,Npar) .* (VarHigh - VarLow) + VarLow; % find the fitness of the solution F(ii)=fitnessFunc(X(ii,:)); end % Main Loop for it=1:MaxIter rng(it); %normalized fitnesss for ii= 1:N Fnorm(ii) = (F(ii) - min(F))/(max(F) - min(F)); end %interaction distance for ii = 1:N for jj = 1:N for kk = 1:Npar D(ii,jj,kk) = (X(ii,kk) - X(jj,kk)); end end end %Moments for ii = 1:N for jj=1:N for kk = 1:Npar p = round(rand*N +0.5); q = round(rand*N +0.5); for dd = 1:Npar DD(dd) = D(ii,jj,dd); end E(ii,jj,kk) = (D(ii,jj,kk)/(1+c1*norm(DD) + c2*D(p,q)))^3; end end end M = E/B; %moment regulation for ii=1:N if (rand<mp) X(ii,:) = X(ii,:) + (XBest - X(ii,:)).*rand(1,Npar); else for jj = 1:Npar r = round(rand*N +0.5); X(ii,jj) = X(r,jj); end end % limit solution within search space X(ii,:) = limiter(X(ii,:),VarHigh,VarLow); % find new fitness F(ii) = fitnessFunc(X(ii,:)); end %MTS Replacement [F, sortOrder] = sort(F); X = X(sortOrder,:); for ii= round(N/2):N if rand<0.5 for jj = 1:Npar r = round(rand*N +0.5); X(ii,jj) = X(ii,jj) + rand*M(ii,r,jj); end else X(ii,:)=rand(1,Npar) .* (VarHigh - VarLow) + VarLow; end % limit solution within search space X(ii,:) = limiter(X(ii,:),VarHigh,VarLow); % find new fitness F(ii) = fitnessFunc(X(ii,:)); end [F, sortOrder] = sort(F); X = X(sortOrder,:); if (F(1) < XBestCost) XBestCost = F(1); XBest = X(1,:); end % store the best value in each iteration GB=[GB XBestCost]; end t1=cputime; fprintf('The time taken is %3.2f seconds \n',t1-t); fprintf('The best value is :'); XBest XBestCost figure plot(0:MaxIter,GB, 'linewidth',1.2); xlabel('Iterations'); ylabel('Objective Function (Cost)'); grid('on')