MATLAB: Particle Swarm Optimization info

data fittingfittinggagenetic algorithmparticle swarmparticle swarm algorithmparticle swarm optimizationpsopswregression

I am trying to find the values of 19 free variables from my data, using the psw optimization algorithm. I got interest in seeing the evolution of the 19 variables together with the minimization of the objective function, over the iterations. I then want to compare this againnst the genetic algorithm.
with the genetic algorithm I am able to to so, and get information (see code below), but with the psw I am no cabable of doing it. With the ga, I call this function from gaoptimset('PlotFcns',{@gaplotbestf, @gapop_func},…
Can you help me with this? Thank you a lot
function [state,options,optchanged] = gapop_func(options,state,flag)
persistent   best r  history_min history_max %h1
optchanged = false;
switch flag
    case 'init'
        best = state.Population;
        assignin('base','gapopbestx',best);
    case 'iter'
        ibest = state.Best(end);
        ibest = find(state.Score == ibest,1,'last');
        bestx = state.Population(ibest,:);
        best = [best; bestx];
        assignin('base','gapop_max_best',history_max);
    case 'done'
       assignin('base','gapopbestx',best);
end

Best Answer

The syntaxes for output functions differ between ga and particleswarm. For an example of a particleswarm output function, see this example. For the correct way to set options for particleswarm, see the same example (you must use optimoptions to set options).
Alan Weiss
MATLAB mathematical toolbox documentation
Related Question