使用ICA的投资组合优化

% % Copyright (c) 2015, Yarpiz (www.yarpiz.com) % All rights reserved. Please read the "license.txt" for license terms. % % Project Code: YPAP112 % Project Title: % Portfolio Optimization using Classic and Intelligent Methods in MATLAB % % Publisher: Yarpiz (www.yarpiz.com) % % Developer: S. Mostapha Kalami Heris (Member of Yarpiz Team) % % Contact Info: sm.kalami@gmail.com, info@yarpiz.com % function out = RunICA(model) %% Problem Definition CostFunction=@(x) PortCost(x,model); % Cost Function nVar=size(model.R,2); % Number of Decision Variables VarSize=[1 nVar]; % Decision Variables Matrix Size VarMin=0; % Lower Bound of Variables VarMax=1; % Upper Bound of Variables %% ICA Parameters MaxIt=150; % Maximum Number of Iterations nPop=40; % Population Size nEmp=5; % Number of Empires/Imperialists alpha=1; % Selection Pressure beta=0.9; % Assimilation Coefficient pRevolution=0.1; % Revolution Probability mu=0.05; % Revolution Rate zeta=0.1; % Colonies Mean Cost Coefficient global ProblemSettings; ProblemSettings.CostFunction=CostFunction; ProblemSettings.nVar=nVar; ProblemSettings.VarSize=VarSize; ProblemSettings.VarMin=VarMin; ProblemSettings.VarMax=VarMax; global ICASettings; ICASettings.MaxIt=MaxIt; ICASettings.nPop=nPop; ICASettings.nEmp=nEmp; ICASettings.alpha=alpha; ICASettings.beta=beta; ICASettings.pRevolution=pRevolution; ICASettings.mu=mu; ICASettings.zeta=zeta; %% Initialization % Initialize Empires emp=CreateInitialEmpires(); % Array to Hold Best Cost Values BestCost=zeros(MaxIt,1); %% ICA Main Loop for it=1:MaxIt % Assimilation emp=AssimilateColonies(emp); % Revolution emp=DoRevolution(emp); % Intra-Empire Competition emp=IntraEmpireCompetition(emp); % Update Total Cost of Empires emp=UpdateTotalCost(emp); % Inter-Empire Competition emp=InterEmpireCompetition(emp); % Update Best Solution Ever Found imp=[emp.Imp]; [~, BestImpIndex]=min([imp.Cost]); BestSol=imp(BestImpIndex); % Update Best Cost BestCost(it)=BestSol.Cost; % Show Iteration Information disp(['Iteration ' num2str(it) ': Best Cost = ' num2str(BestCost(it))]); end %% Results out.BestSol=BestSol; out.BestCost=BestCost; end