matlab程序.zip_测试函数

function [InitFunction, CostFunction, FeasibleFunction] = Penalty2 InitFunction = @Penalty2Init; CostFunction = @Penalty2Cost; FeasibleFunction = @Penalty2Feasible; return; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [MaxParValue, MinParValue, Population, OPTIONS] = Penalty2Init(OPTIONS) global MinParValue MaxParValue Granularity = 0.1; MinParValue = 1; MaxParValue = floor(1 + 2 * 50 / Granularity); % Initialize population for popindex = 1 : OPTIONS.popsize chrom = floor(MinParValue + (MaxParValue - MinParValue + 1) * rand(1,OPTIONS.numVar)); Population(popindex).chrom = chrom; end OPTIONS.OrderDependent = true; return; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [Population] = Penalty2Cost(OPTIONS, Population) % Compute the cost of each member in Population global MinParValue MaxParValue for popindex = 1 : OPTIONS.popsize Population(popindex).cost = 0; for i = 1 : OPTIONS.numVar gene = Population(popindex).chrom(i); x(i) = (gene - MinParValue) / (MaxParValue - MinParValue) * 2 * 50 - 50; if (x(i) > 5) u = 100 * (x(i) - 5)^4; elseif (x(i) < -5) u = 100 * (-x(i) - 5)^4; else u = 0; end Population(popindex).cost = Population(popindex).cost + u; end Population(popindex).cost = Population(popindex).cost + 0.1 * ((sin(pi*3*x(1)))^2 + (x(OPTIONS.numVar) - 1)^2 * (1 + (sin(2*pi*x(OPTIONS.numVar)))^2)); for i = 1 : OPTIONS.numVar-1 Population(popindex).cost = Population(popindex).cost + 0.1 * ((x(i) - 1)^2 * (1 + (sin(3*pi*x(i+1)))^2)); end end return %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [Population] = Penalty2Feasible(OPTIONS, Population) global MinParValue MaxParValue for i = 1 : OPTIONS.popsize for k = 1 : OPTIONS.numVar Population(i).chrom(k) = max(Population(i).chrom(k), MinParValue); Population(i).chrom(k) = min(Population(i).chrom(k), MaxParValue); end end return;