蜜蜂算法(BeA).zip_MATLAB蜜蜂算法_优化算法_蜜蜂算法

% %来源：https://ww2.mathworks.cn/matlabcentral/fileexchange/52967-bees-algorithm-bea-in-matlab?s_tid=prof_contriblnk % % Copyright (c) 2015, Yarpiz (www.yarpiz.com) % All rights reserved. Please read the "license.txt" for license terms. % % Project Code: YPEA115 % Project Title: Implementation of Standard Bees Algorithm in MATLAB % Publisher: Yarpiz (www.yarpiz.com) % % Developer: S. Mostapha Kalami Heris (Member of Yarpiz Team) % % Contact Info: sm.kalami@gmail.com, info@yarpiz.com % clc; clear; close all; %% Problem Definition CostFunction=@(x) Sphere(x); % Cost Function nVar=5; % Number of Decision Variables VarSize=[1 nVar]; % Decision Variables Matrix Size VarMin=-10; % Decision Variables Lower Bound VarMax= 10; % Decision Variables Upper Bound %% Bees Algorithm Parameters MaxIt=1000; % Maximum Number of Iterations nScoutBee=30; % Number of Scout Bees nSelectedSite=round(0.5*nScoutBee); % Number of Selected Sites nEliteSite=round(0.4*nSelectedSite); % Number of Selected Elite Sites nSelectedSiteBee=round(0.5*nScoutBee); % Number of Recruited Bees for Selected Sites nEliteSiteBee=2*nSelectedSiteBee; % Number of Recruited Bees for Elite Sites r=0.1*(VarMax-VarMin); % Neighborhood Radius rdamp=0.95; % Neighborhood Radius Damp Rate %% Initialization % Empty Bee Structure empty_bee.Position=[]; empty_bee.Cost=[]; % Initialize Bees Array bee=repmat(empty_bee,nScoutBee,1); % Create New Solutions for i=1:nScoutBee bee(i).Position=unifrnd(VarMin,VarMax,VarSize); bee(i).Cost=CostFunction(bee(i).Position); end % Sort [~, SortOrder]=sort([bee.Cost]); bee=bee(SortOrder); % Update Best Solution Ever Found BestSol=bee(1); % Array to Hold Best Cost Values BestCost=zeros(MaxIt,1); %% Bees Algorithm Main Loop for it=1:MaxIt % Elite Sites for i=1:nEliteSite bestnewbee.Cost=inf; for j=1:nEliteSiteBee newbee.Position=PerformBeeDance(bee(i).Position,r); newbee.Cost=CostFunction(newbee.Position); if newbee.Cost<bestnewbee.Cost bestnewbee=newbee; end end if bestnewbee.Cost<bee(i).Cost bee(i)=bestnewbee; end end % Selected Non-Elite Sites for i=nEliteSite+1:nSelectedSite bestnewbee.Cost=inf; for j=1:nSelectedSiteBee newbee.Position=PerformBeeDance(bee(i).Position,r); newbee.Cost=CostFunction(newbee.Position); if newbee.Cost<bestnewbee.Cost bestnewbee=newbee; end end if bestnewbee.Cost<bee(i).Cost bee(i)=bestnewbee; end end % Non-Selected Sites for i=nSelectedSite+1:nScoutBee bee(i).Position=unifrnd(VarMin,VarMax,VarSize); bee(i).Cost=CostFunction(bee(i).Position); end % Sort [~, SortOrder]=sort([bee.Cost]); bee=bee(SortOrder); % Update Best Solution Ever Found BestSol=bee(1); % Store Best Cost Ever Found BestCost(it)=BestSol.Cost; % Display Iteration Information disp(['Iteration ' num2str(it) ': Best Cost = ' num2str(BestCost(it))]); % Damp Neighborhood Radius r=r*rdamp; end %% Results figure; %plot(BestCost,'LineWidth',2); semilogy(BestCost,'LineWidth',2); xlabel('Iteration'); ylabel('Best Cost');