Genetic Algorithm Custom Output

Question

Burak Bayca 2025-1-27

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2173346-genetic-algorithm-custom-output

回答： Alan Weiss 2025-1-29

Hello, I'm trying to optimize a simple Simulink model output by using Genetic Algorithm. Three different output values are implemented in this model. The first one is used as cost value. Hovewer, the other two values are not assigned to anything. I want to get these outputs as timeseries after the Genetic Algorithm calculations, like "The second output of Generation XX Individual YY is ...". When the calculations are done with single core, I can get all the results I want, but when the parallel toolbox is used, only the last generation and last individual is visible after the calculations. How can I fix that parallel calculation? Here is my simple code that gives all individuals and cost values for me, but I need the other two outputs of simulation. Thanks.

clear all;clc;,
%%
tic
saveFlag = 0;
rng('shuffle');
objectiveFunction = @(params) nlaSimResults(params);
lowerBound = [1000 0.2];
upperBound = [25000 0.8];
popSize = 10;
genSize = 20;
options = optimoptions('ga','UseParallel',true,'UseVectorized',false,'PopulationSize',popSize,'MaxGenerations',genSize,'OutputFcn',@gaOutputFunction,'Display','iter');
[bestParams, minCost, ~, optResults, optPop, optScores] = ga(objectiveFunction,2,[],[],[],[],lowerBound,upperBound,[],options);
optimTime = toc;
if saveFlag == 1; save('OptimResulst','bestParams','minCost','optResults','optScores','optimTime','popSize','genSize'); end
function cost = nlaSimResults(params)
    global otherVars
    
    Altitude = params(1);
    Mach = params(2);
    assignin('base','Altitude',Altitude);
    assignin('base','Mach',Mach);
    sim('debugModel',10); % Simulation Model with Altitude and Mach inputs
    cost = logsout{1}.Values.Data(1); % The first output of the model is assigned as cost
    
    if isempty(otherVars)
        otherVars = {};
    end
    otherVars = [otherVars; logsout{2}.Values.Data logsout{3}.Values.Data];
    assignin('base','otherVars',otherVars);
end
function [state, options, flag] = gaOutputFunction(options, state, flag)
    persistent popHistory bestValues bestIndividuals otherVarsHistory
    global otherVars
    if isempty(popHistory)
        popHistory = {};
        bestValues = [];
        bestIndividuals = [];
        otherVarsHistory = {};
    end
    [bestScore, bestIdx] = min(state.Score);
    bestValues = [bestValues; bestScore];
    bestIndividuals = [bestIndividuals; state.Population(bestIdx, :)];
    popHistory(state.Generation + 1) = {state.Population};
    otherVarsHistory{state.Generation + 1} = otherVars;
    otherVars = [];
    assignin('base','popHistory',popHistory);
    assignin('base','bestValues',bestValues);
    assignin('base','bestIndividuals',bestIndividuals);
    assignin('base','otherVarsHistory',otherVarsHistory);
end