clc clear all pack %%%%%%%%%% n is dimension of objective function n = 30; %%%%%%%%%% Define the Range of Variables Xmax = ones(1,n) ×100; Xmin = ones(1,n)*(−100); %%%%%%%%%% n is the Population Size N = 150; %%%%%%%%%% Maximum Numbe od Iteration Iter_max = 500; %%%%%%%%%% Define the GBFIO prameters f = 2.5; eta = 1.25; Zeta = 0.3; fishing_number = 25; %%%%%%%%%% Generate the Initial Populations for i = 1:N   Ipop(i,:) = rand(1,n).*(Xmax − Xmin) + Xmin;   cost(i,:) = sum(Ipop(i,:).^2); end %%%%%%%%%% Sort the Initial Populations Based on Cost Function Ipop_mix = [Ipop,cost]; Ipop_sort = sortrows(Ipop_mix,n + 1); %%%%%%%%%% Specify the Fish, Honey, Body, Shell, and Plants Fish = Ipop_sort(1,:); Honey = Ipop_sort(2,:); Body = Ipop_sort(3,:); Shell = Ipop_sort(4,:); Plants = Ipop_sort(5,:); %%%%%%%%%% Start the Iterationa for Updating Populations for iter = 1:Iter_max   for i = 1:N     %%%%%%%%%% Start the Searching Phase     r1 = rand(1,n);     deltax_fish = (2.*r1.*( (r1).^0.5)).*(Fish(1,[1:n]) − Ipop(i,:));     deltax_honey = (r1.*((r1).^0.5)).*(Honey(1,[1:n]) − Ipop(i,:));     deltax_body = (0.5.*r1.*((r1).^0.5)).*(Body(1,[1:n]) − Ipop(i,:));     deltax_shell = (0.25.*r1.*((r1).^0.5)).*(Shell(1,[1:n]) − Ipop(i,:));     deltax_plants = (0.125.*r1.*((r1).^0.5)).*(Plants(1,[1:n]) − Ipop(i,:)); Xnew_search = Ipop(i,:) + deltax_fish + deltax_honey + deltax_body + deltax_shell + deltax_plants;     Xnew_search = min(Xnew_search,Xmax);     Xnew_search = max(Xnew_search,Xmin); cost_S = sum(Xnew_search.^2);     %%%%%%%%%% Update the Population     if cost_S < cost(i,1)       Ipop(i,:) = Xnew_search;       cost(i,1) = cost_S;     end     %%%%%%%%%% End the Searching Phase     %%%%%%%%%% Start the Hunting Phase     %%%%% Start the Hunting Phase: Bear Hunting     Ipop_mix = [Ipop,cost];     Ipop_sort = sortrows(Ipop_mix,n + 1);     Prey = Ipop_sort(1,:);     A = (f*(1-iter/Iter_max)).*(2.*rand(1,n) − 1);     D = abs(((2.*rand(1,n)).*Ipop(i,:))-(rand(1,n).*Prey(1,[1:n])));     X_hunt = Ipop(i,:)-A.*D;     X_hunt = min(X_hunt,Xmax);     X_hunt = max(X_hunt,Xmin);     cost_hunt = sum(X_hunt.^2);     %%%%% Start the Hunting Phase: Coyote Hunting     L = randperm(N);     LL = find(L~ = i);     LLL = L(LL);     J1 = LL(1);     J2 = LL(2);     J3 = LL(3);     I_child = [Ipop(J1,:),cost(J1,1);Ipop(J2,:),cost(J2,1);Ipop(J3,:),cost(J3,1)];     I_chsort = sortrows(I_child,n + 1);     A1 = (eta*(1-iter/Iter_max)).*(2.*rand(1,n) − 1);     A2 = (eta*(1-iter/Iter_max)).*(2.*rand(1,n) − 1);     D1 = abs(((2.*rand(1,n)).*I_chsort(2,[1:n])) − (rand(1,n).*I_chsort(1,[1:n])));     D2 = abs(((2.*rand(1,n)).*I_chsort(3,[1:n])) − (rand(1,n).*I_chsort(1,[1:n])));     X_ch = Ipop(i,:) − (A1.*D1 + A2.*D2);     X_ch = min(X_ch,Xmax);     X_ch = max(X_ch,Xmin);     cost_ch = sum(X_ch.^2);     %%%%%%%%%% Update the Population     G = rand(1,1);     if G < 0.75       if cost_hunt < cost(i,1)         Ipop(i,:) = X_hunt;         cost(i,1) = cost_hunt;       end     else       if cost_ch < cost(i,1)         Ipop(i,:) = X_ch;         cost(i,1) = cost_ch;       end     end     %%%%%%%%%% End the Hunting Phase     %%%%%%%%%% Start the Fishing Phase     for kk = 1:fishing_number       Z = Zeta*(1 − iter/Iter_max)*cos(2*pi*rand(1,1));       X_fish = (1 + Z).*Ipop(i,:);       X_fish = min(X_fish,Xmax);       X_fish = max(X_fish,Xmin);       cost_fishing = sum(X_fish.^2);       %%%%%%%%%% Update the Population       if cost_fishing < cost(i,1)         Ipop(i,:) = X_fish;         cost(i,1) = cost_fishing;       end     end     %%%%%%%%%% Specify the Fish, Honey, Body, Shell, and Plants for     Ipop_mix = [Ipop,cost];     Ipop_sort = sortrows(Ipop_mix,n + 1);     Fish = Ipop_sort(1,:);     Honey = Ipop_sort(2,:);     Body = Ipop_sort(3,:);     Shell = Ipop_sort(4,:);     Plants = Ipop_sort(5,:);   end   %%%%%%%%%% Specify the Parameters of Convergence Curve   Convergence_Curve(iter,1) = iter;   Convergence_Curve(iter,2) = Ipop_sort(1,n + 1); end %%%%%%%%%% Print the Best Soultion Best = Ipop_sort(1,:) plot(Convergence_Curve(:,1),Convergence_Curve(:,2))