基于细菌觅食算法BFO解决经济调度问题附matlab代码.zip

% Bacteria foraging algorithm for economic dispatch problem with VALVE POINT LOADING % % by S.PRAVEEN KUMAR EMAIL:[email protected] phone +918074630423,+919959022691 % clear all; close all; clc; diary prav; % Bacteria Foraging Optimization % % ------- initialisation ----------% Pd=1800; Ne=200;%no of iteration Nr=20; Nc=20; Np=30;%population size Ns=10; D=13;% no of generator units C=0.001; Ped=0.9; ; % elimination dispersion probability cost=[550 8.10 0.00028 00 680 300 0.035 309 8.10 0.00056 00 360 200 0.042 307 8.10 0.00056 00 360 200 0.042 240 7.74 0.00324 60 180 150 0.063 240 7.74 0.00324 60 180 150 0.063 240 7.74 0.00324 60 180 150 0.063 240 7.74 0.00324 60 180 150 0.063 240 7.74 0.00324 60 180 150 0.063 240 7.74 0.00324 60 180 150 0.063 126 8.6 0.00284 40 120 100 0.084 126 8.6 0.00284 40 120 100 0.084 126 8.6 0.00284 55 120 100 0.084 126 8.6 0.00284 55 120 100 0.084]; a=cost(:,1); b=cost(:,2); c=cost(:,3); Pmin=cost(:,4); Pmax=cost(:,5); ee=cost(:,6); ff=cost(:,7); % bfoinit; for k=1:Np for i=1:D x(k,i)=Pmin(i)+rand*(Pmax(i)-Pmin(i)); end end %x % x=(rand(Np,D)-0.5)*60 % x lies in [-30 30] J=zeros(Np,1); for k=1:Np temp1=0; temp5=0; for i=1:D temp1=temp1+x(k,i); temp5=temp5+a(i)+b(i)*x(k,i)+c(i)*x(k,i)*x(k,i)+abs(ee(i)*sin(ff(i)*(Pmin(i)-x(k,i)))); % J(k)=sum(100*(x(k,i+1)-x(k,i)^2)^2+(x(k,i)-1)^2); % initial fitness calculation end temp2=Pd-temp1; temp3=0; if(temp2>0) temp3=200.0*temp2; end J(k)=temp5+temp3; end J; Jlast=J; for l=1:Ne for k=1:Nr Jchem=J; for j=1:Nc % Chemotaxis Loop % for i=1:Np del=(rand(1,D)-0.5)*2; x(i,:)=x(i,:)+(C/sqrt(del*del'))*del; temp1=0; temp5=0; for d=1:D if(x(i,d)<Pmin(d)) x(i,d)=Pmin(d); end if(x(i,d)>Pmax(d)) x(i,d)=Pmax(d); end temp1=temp1+x(i,d); temp5=temp5+a(d)+b(d)*x(i,d)+c(d)*x(i,d)*x(i,d)+abs(ee(d)*sin(ff(d)*(Pmin(d)-x(i,d)))); %J(i)=sum(100*(x(i,d+1)-x(i,d)^2)^2+(x(i,d)-1)^2); end temp2=Pd-temp1; temp3=0; if(temp2>0) temp3=200.0*temp2; end J(i)=temp5+temp3; for m=1:Ns if J(i)<Jlast(i) Jlast(i)=J(i); x(i,:)=x(i,:)+C*(del/sqrt(del*del')); temp1=0; temp5=0; for d=1:D if(x(i,d)<Pmin(d)) x(i,d)=Pmin(d); end if(x(i,d)>Pmax(d)) x(i,d)=Pmax(d); end temp1=temp1+x(i,d); temp5=temp5+a(d)+b(d)*x(i,d)+c(d)*x(i,d)*x(i,d)+abs(ee(d)*sin(ff(d)*(Pmin(d)-x(i,d)))); % J(i)=sum(100*(x(i,d+1)-x(i,d)^2)^2+(x(i,d)-1)^2); end temp2=Pd-temp1; temp3=0; if(temp2>0) temp3=200.0*temp2; end J(i)=temp5+temp3; else del=(rand(1,D)-0.5)*2; x(i,:)=x(i,:)+C*(del/sqrt(del*del')); temp1=0; temp5=0; for d=1:D if(x(i,d)<Pmin(d)) x(i,d)=Pmin(d); end if(x(i,d)>Pmax(d)) x(i,d)=Pmax(d); end temp1=temp1+x(i,d); temp5=temp5+a(d)+b(d)*x(i,d)+c(d)*x(i,d)*x(i,d)+abs(ee(d)*sin(ff(d)*(Pmin(d)-x(i,d)))); % J(i)=sum(100*(x(i,d+1)-x(i,d)^2)^2+(x(i,d)-1)^2); end temp2=Pd-temp1; temp3=0; if(temp2>0) temp3=200.0*temp2; end J(i)=temp5+temp3; end end end Jchem=[Jchem J]; end % End of Chemotaxis % for i=1:Np Jhealth(i)=sum(Jchem(i,:)); % sum of cost function of all chemotactic loops for a given k & l end [Jhealth1,I]=sort(Jhealth,'ascend'); x=[x(I(1:Np/2),:);x(I(1:Np/2),:)]; J=[J(I(1:Np/2),:);J(I(1:Np/2),:)]; xmin=x(I(1),:); end Jmin(l)=min(J); % random elimination dispersion for i=1:Np r=rand; if r>=Ped x(i,:)=(rand(1,D)-0.5); temp1=0; temp5=0; for d=1:D if(x(i,d)<Pmin(d)) x(i,d)=Pmin(d); end if(x(i,d)>Pmax(d)) x(i,d)=Pmax(d); end temp1=temp1+x(i,d); temp5=temp5+a(d)+b(d)*x(i,d)+c(d)*x(i,d)*x(i,d)+abs(ee(d)*sin(ff(d)*(Pmin(d)-x(i,d)))); % J(i)=sum(100*(x(i,d+1)-x(i,d)^2)^2+(x(i,d)-1)^2); end temp2=Pd-temp1; temp3=0; if(temp2>0) temp3=200.0*temp2; end J(i)=temp5+temp3; end end end Jmin plot(Jmin); xmin Pg= sum(xmin)