GSK_for_PV_models.zip

% clc % clear all function GSK % population size setting % m = 50; global m runnum ELD Max_FEs %runnum: the number of trial runs % runnum =1; KF = 0.5; % Knowledge Factor KR = 0.9; %Knowledge Ratio K = 10; %Knowledge Rate p = 0.1; KRmax = 0.9; KRmin = 0.3; KFmax = 0.9; KFmin = 0.3; % Max_FEs = d * 10000; % Max_gen = Max_FEs / m; FE_NM = m; [Max_gen, MaxParValue, MinParValue, d] = Problem(ELD,m); Max_gen = round(Max_gen); finalresults = []; % Max_FEs = 50000; results = zeros(runnum,Max_gen); solution = []; % several runs for run = 1 : runnum run %%% Initialize Population %%% Population = repmat(MinParValue,m,1) + rand(m,d) .* repmat((MaxParValue - MinParValue),m,1); TempPop = zeros (m , d); % Temporary population [Objective_values, Population] = fitness(Population,ELD); bestever = 1e200; FEs = m; % Sort Population % [Population,Objective_values] = PopulationSort(Population,Objective_values); % pbest = Population; pbestval = Objective_values; %initialize the pbest and the pbest's fitness value [gbestval,gbestid] = min(pbestval); best = Population(gbestid,:); % gbest = pbest(gbestid,:); %initialize the gbest and the gbest's fitness value %=========================================================================% %%% BBO Main Loop %%% % FES = m; gen = 0; results = []; tic; % main loop % while(gen < Max_gen) while(FEs < Max_FEs) % fi = cos((pi*FEs) / (2*Max_FEs)); % KF = fi * KFmax + (1 - fi) * KFmin; % KR = (1 - fi) * KRmax + fi * KRmin; % Sort Population [Population,Objective_values] = PopulationSort(Population,Objective_values); D_Gained_Shared_Junior = ceil(d*(1 - FEs / Max_FEs)^K); % D_Gained_Shared_Senior = d - D_Gained_Shared_Junior; % Use migration rates to GSKciGSK how much information to share between solutions for i = 1 : m % Gained_Shared_Junior_R1R2R3 if(i==1)% best r1_Junior = 2; r2_Junior = 3; elseif(i == m)% worst r1_Junior = m - 2; r2_Junior = m - 1; else r1_Junior = i - 1; r2_Junior = i + 1; end while true r3_Junior = round(m * rand + 0.5); if (r3_Junior ~= r1_Junior) && (r3_Junior ~= r2_Junior) && (r3_Junior ~= i) , break, end end % Gained_Shared_Senior_R1R2R3 r1_Senior = ceil(p*m * rand); r2_Senior = ceil((1-p) * m) + ceil(p*m * rand); while true r3_Senior = ceil(p * m) + ceil((1-2*p)*m * rand); if (r3_Senior ~= i), break, end end for j = 1:d if (rand < KR) if rand < D_Gained_Shared_Junior/d if i < r3_Junior TempPop(i,j) = Population(i,j) + KF * (Population(r1_Junior,j) - Population(r2_Junior,j)) + ... KF * (Population(i,j) - Population(r3_Junior,j)); else TempPop(i,j) = Population(i,j) + KF * (Population(r1_Junior,j) - Population(r2_Junior,j)) + ... KF * (Population(r3_Junior,j) - Population(i,j)); end else if i < r3_Senior TempPop(i,j) = Population(i,j) + KF * (Population(r1_Senior,j) - Population(r2_Senior,j)) + ... KF * (Population(i,j) - Population(r3_Senior,j)); else TempPop(i,j) = Population(i,j) + KF * (Population(r1_Senior,j) - Population(r2_Senior,j)) + ... KF * (Population(r3_Senior,j) - Population(i,j)); end end else TempPop(i,j) = Population(i,j); end end end % Evaluation [Objective_values_TempPop, TempPop] = fitness(TempPop,ELD); FEs = FEs + m; % Comparision mask = Objective_values_TempPop < Objective_values; aa = repmat(mask',1,d); Population = aa .* TempPop + ~aa .* Population; Objective_values = mask .* Objective_values_TempPop + ~mask .* Objective_values; [gbestval,gbestid] = min(Objective_values); best = Population(gbestid,:); MinimumCost = gbestval; bestsolution = Population(gbestid,:); % Display Iteration Information gen = gen + 1; % results(run,gen) = MinimumCost; results = [results; MinimumCost]; % fprintf('Best fitness: %e gen %d\n', MinimumCost,gen); % fprintf('Best fitness: %e and avg: %e gen %d\n', MinimumCost, mean(Objective_values), gen); end xx = round(linspace(1,length(results),100)); finalresults = [finalresults results(xx)]; solution = [solution; bestsolution]; fprintf('Run No.%d Done!\n', run); disp(['CPU time: ',num2str(toc)]); end Maxresult = max(finalresults(end,1:runnum)); Meanresult = mean(finalresults(end,1:runnum)); Minresult = min(finalresults(end,1:runnum)); stdresult = std(finalresults(end,1:runnum)); Allresults = [Minresult; Maxresult; Meanresult; stdresult]; Allresults_GSK = Allresults; results_GSK = [finalresults]; solution_GSK = solution'; str2='Allresults_GSK'; str3=strcat(str2, num2str(ELD), '.xls'); xlswrite( str3, Allresults_GSK') ; str2='results_GSK'; str3=strcat(str2, num2str(ELD), '.xls'); xlswrite( str3, results_GSK) ; str2='solution_GSK'; str3=strcat(str2, num2str(ELD),'.xls'); xlswrite( str3, solution_GSK) ; return