- Pass the whole population to the objective function. This is done by setting the UseVectorized option to true.
- When the whole population is received by the objective function, it must create a SimulationInput object. You can learn about creating it here. Your SimulationInput object is an array, where each element represents a chromosome in the population.
- Then you pass the single SimulationInput object to parsim().
- Next, simulations are run and the SimulationOutput object is returned.
- Finally, you calculate the objective function values from the SimulationOutput object and return them to the solver.
Get parallel simulations in objective function of optimization Tool (GA,PSO)
조회 수: 19(최근 30일)
i have an optimization problem using the constrainted PSO:
The syntax and general working of the constrainted PSO is the same as GA.
In my objective function, i have to generate a simOut with data from a simulink simulation. One calculation needs about 7 hours of time, since the simulation needs about 3 seconds.To increase the algorithm speed, i want the simulations to run parallel. But it doesnt seem to work if i use "parpool('local')". So far ich changed the settings to "UseVectorized" so have the whole population in one objective function. My code looks like this:
options = psooptimset('Display','iter','OutputFcns',@myoutputFunc,'UseParallel',true,...
[xopt,fval,exitflag,output,population,scores] = pso(@objective,9,,,,,lb,ub,@constraint,options);
function obj = objective(x)
% WANT TO: check the number of workers , in my case 6
% WANT TO: set parallel simulations equal to work number
for p=1:length(x(:,1)) %WANT TO: set parallel working parfor loop to execute the parallel simulations
SimuGeometrics = calculateGeometrics(x(p,:)); %SimuGeometrics is a structure of lengths and angle of different body that are used for simulink
simOut = sim('Mechanism.slx','CaptureErrors','on','SrcWorkspace','current');
pos1 = [simOut.xx.data, simOut.yy.data, simOut.zz.data];
obj(p,1) = calculateDeviation(pos1);
disp(['x: ',num2str(x(p,:)) ,' obj: ',num2str(obj(p,1))]);
I know that there are some functions like parfor or parsim but i dont know how to include them into my Code.
Of cause, my WANTO TO's are only ideas how i think it can work, if for example setting a parfor loop is nonsense, you can suggest another solution
i saw your Answer from :https://de.mathworks.com/matlabcentral/answers/595402-how-to-use-the-parallel-computing-toolbox-of-matlab-to-optimize-the-parameters-of-a-simulink-model-w#answer_496378
it seems like you described a possible solution for my problem. I will try out what you described today and will share my solution if i succeed, but it would help me alot if u could share your expertise on this.
I hope somebody can help me with this problem.
Abdolkarim Mohammadi 2021년 2월 12일
I haven't used that File Exchange submission for PSO, but the general workflow in such situations is to:
The objective funciton's code might look something like this:
function f = ObjFun(x)
% get population size
PopulationSize = size(x, 1);
% create the SimluationInput object
for i1 = 1:PopulationSize
SimIn(i1) = Simulink.SimulationInput('MyModel');
SimIn(i1) = SimIn(i1).setVariable('MyVar1', x(i1,1))
SimIn(i1) = SimIn(i1).setVariable('MyVar2', x(i1,2))
% do it for all of the variables
% run the simulations and get the SimulationOutput object
SimOut = parsim(SimIn);
% initialize the arrays containing the objective function values
f = zeros (PopulationSize, 1);
% fill f with objective function values
for i1 = 1:PopulationSize
f(i1) = SimOut(i1).MyOutput;
Read about setVariable function here.