含仿真录像，基于和声搜索算法的sphere函数极值搜索matlab仿真

clc; clear; close all; warning off; addpath(genpath(pwd)); %% Problem Definition CostFunction = @(x) Sphere(x); % Cost Function nVar = 5; % Number of Deciison Variables VarSize = [1 nVar]; % Decision Variables Matrix Size VarMin = -10; % Decision Variables Lower Bound VarMax = 10; % Decision Variables Upper Bound %% Harmony Search Parameters MaxIt = 5000; % Maximum Number of Iterations,5000 HMS = 25; % Harmony Memory Size nNew = 20; % Number of New Harmonies HMCR = 0.9; % Harmony Memory Consideration Rate PAR = 0.1; % Pitch Adjustment Rate FW = 0.02*(VarMax-VarMin); % Fret Width (Bandwidth) FW_damp = 0.995; % Fret Width Damp Ratio %% Initialization % Empty Harmony Structure empty_harmony.Position = []; empty_harmony.Cost = []; % Initialize Harmony Memory HM = repmat(empty_harmony, HMS, 1); % Create Initial Harmonies for i = 1:HMS HM(i).Position = unifrnd(VarMin, VarMax, VarSize); HM(i).Cost = CostFunction(HM(i).Position); end % Sort Harmony Memory [~, SortOrder] = sort([HM.Cost]); HM = HM(SortOrder); % Update Best Solution Ever Found BestSol = HM(1); % Array to Hold Best Cost Values BestCost = zeros(MaxIt, 1); %% Harmony Search Main Loop for it = 1:MaxIt % Initialize Array for New Harmonies NEW = repmat(empty_harmony, nNew, 1); % Create New Harmonies for k = 1:nNew % Create New Harmony Position NEW(k).Position = unifrnd(VarMin, VarMax, VarSize); for j = 1:nVar if rand <= HMCR % Use Harmony Memory i = randi([1 HMS]); NEW(k).Position(j) = HM(i).Position(j); end % Pitch Adjustment if rand <= PAR %DELTA = FW*unifrnd(-1, +1); % Uniform DELTA = FW*randn(); % Gaussian (Normal) NEW(k).Position(j) = NEW(k).Position(j)+DELTA; end end % Apply Variable Limits NEW(k).Position = max(NEW(k).Position, VarMin); NEW(k).Position = min(NEW(k).Position, VarMax); % Evaluation NEW(k).Cost = CostFunction(NEW(k).Position); end % Merge Harmony Memory and New Harmonies HM = [HM NEW]; %#ok % Sort Harmony Memory [~, SortOrder] = sort([HM.Cost]); HM = HM(SortOrder); % Truncate Extra Harmonies HM = HM(1:HMS); % Update Best Solution Ever Found BestSol = HM(1); % Store Best Cost Ever Found BestCost(it) = BestSol.Cost; % Show Iteration Information disp(['Iteration ' num2str(it) ': Best Cost = ' num2str(BestCost(it))]); % Damp Fret Width FW = FW*FW_damp; end %% Results figure; % plot(BestCost, 'LineWidth', 2); semilogy(BestCost, 'LineWidth', 2); xlabel('Iteration'); ylabel('Best Cost'); grid on;