【智能优化算法-蝠鲼觅食优化算法】基于改进蝠鲼觅食优化算法dFDB_MRFO求解最优目标附matlab代码.zip

function []=dFDB_MRFO() [nPop, Dim, maxIteration, Low, Up] = problem_terminate(); MaxIt = ceil((maxIteration/ (nPop*2))); PopPos = zeros(nPop,Dim); PopFit = zeros(1,nPop); newPopFit = zeros(1,nPop); for i=1:nPop PopPos(i,:) = rand(1,Dim).*(Up-Low)+Low; PopFit(i) = problem(PopPos(i,:)); end BestF=inf; BestX=[]; for i=1:nPop if PopFit(i)<=BestF BestF=PopFit(i); BestX=PopPos(i,:); end end for It=1:MaxIt Coef=It/MaxIt; if rand<0.5 r1=rand; Beta=2*exp(r1*((MaxIt-It+1)/MaxIt))*(sin(2*pi*r1)); if Coef>rand newPopPos(1,:)=BestX+rand(1,Dim).*(BestX-PopPos(1,:))+Beta*(BestX-PopPos(1,:)); %Equation (4) else IndivRand=rand(1,Dim).*(Up-Low)+Low; newPopPos(1,:)=IndivRand+rand(1,Dim).*(IndivRand-PopPos(1,:))+Beta*(IndivRand-PopPos(1,:)); %Equation (7) end else Alpha=2*rand(1,Dim).*(-log(rand(1,Dim))).^0.5; newPopPos(1,:)=PopPos(1,:)+rand(1,Dim).*(BestX-PopPos(1,:))+Alpha.*(BestX-PopPos(1,:)); %Equation (1) end fdbIndex = dFDB( PopPos, PopFit, 10,It,MaxIt); for i=2:nPop if rand<0.5 r1=rand; Beta=2*exp(r1*((MaxIt-It+1)/MaxIt))*(sin(2*pi*r1)); if Coef>rand newPopPos(i,:)=BestX+rand(1,Dim).*(PopPos(i-1,:)-PopPos(i,:))+Beta*(BestX-PopPos(i,:)); %Equation (4) else IndivRand=rand(1,Dim).*(Up-Low)+Low; newPopPos(i,:)=IndivRand+rand(1,Dim).*(PopPos(i-1,:)-PopPos(i,:))+Beta*(IndivRand-PopPos(i,:)); %Equation (7) end else Alpha=2*rand(1,Dim).*(-log(rand(1,Dim))).^0.5; if rand<0.5 newPopPos(i,:)=PopPos(i,:)+rand(1,Dim).*(PopPos(i-1,:)-PopPos(i,:))+Alpha.*(PopPos(fdbIndex,:)-PopPos(i,:)); %Equation (1) else newPopPos(i,:)=PopPos(i,:)+rand(1,Dim).*(PopPos(i-1,:)-PopPos(i,:))+Alpha.*(BestX-PopPos(i,:)); %Equation (1) end end end for i=1:nPop newPopPos(i,:)=SpaceBound(newPopPos(i,:),Up,Low); newPopFit(i)=problem(newPopPos(i,:)); if newPopFit(i)<PopFit(i) PopFit(i)=newPopFit(i); PopPos(i,:)=newPopPos(i,:); end end S=2; for i=1:nPop newPopPos(i,:)=PopPos(i,:)+S*(rand*BestX-rand*PopPos(i,:)); %Equation (8) end for i=1:nPop newPopPos(i,:)=SpaceBound(newPopPos(i,:),Up,Low); newPopFit(i)=problem(newPopPos(i,:)); if newPopFit(i)<PopFit(i) PopFit(i)=newPopFit(i); PopPos(i,:)=newPopPos(i,:); end end for i=1:nPop if PopFit(i)<BestF BestF=PopFit(i); BestX=PopPos(i,:); end end end fprintf('Best Fitness: %d\n', BestF); disp('Best Solution:'); disp(BestX); end function X=SpaceBound(X,Up,Low) Dim=length(X); S=(X>Up)+(X<Low); X=(rand(1,Dim).*(Up-Low)+Low).*S+X.*(~S); end