[HELP] fmincon to ga

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E K 2012-7-31

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https://ww2.mathworks.cn/matlabcentral/answers/44965-help-fmincon-to-ga

评论： Nouhaila Lazaar 2020-11-3

Hi guys,

I have a o object function that i write for fmincon.

What should i change to minimize same object function by a ga(genetic algorithm) any tips,suggestions will be amazingly help me.

I explained the functions/problem/object (fitness) function better in comments below.

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Answer 1

Sean de Wolski 2012-7-31

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You shouldn't have to change anything!

In fact you can use ga as the coarse minimization method and then use fmincon as a 'HybridFcn' for the finer tuned minimization after ga has gotten close.

doc gaoptimset

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E K 2012-7-31

编辑：E K 2012-7-31

在 MATLAB Online 中打开

Hi again sean and thank for your patience and help. i am pretty lost in these optimisation processes.

i am pasting some codes to make a clear explanation

This is my setup/initial function (or where the problem begins) i got the parts of the code from an example.

%{

 function  [dim,lb,ub,x0] = celltowersetup(N,up,seed) 
% CELLTOWERSETUP creates a randomly generated celltower problem.
%   [dim,lb,ub,x0] = CELLTOWERSETUP(N, SIDE, SEED)
%
%   Input:
%           N    : number of towers
%           SIDE : length of the side of area
%           SEED : random seed for initial cell location (integer)
%   Output:
%           dim.R    : radius of cell tower coverage
%           dim.xL   : 0       % for plotting
%           dim.xU   : SIDE    % for plotting
%           dim.yL   : 0       % for plotting
%           dim.yU   : SIDE    % for plotting
%           lb       : lower bound values for x, y (based on the radius)
%           ub       : upper bound values for x, y (based on the radius) 
%           x0       : initial center points (x, y pairs)
 low = 0;
st = RandStream('mcg16807', 'Seed', seed);
R = rand(st, N,1)+1; % allocate array
 % Generate bound constraints
xL = low; xU = up;
yL = low; yU = up;
% 2*N variables in the order [x1,y1,x2,y2...,xn,yn]'
lb = zeros(2*N,1);
ub = lb;
lb(1:2:2*N) = xL + R;
lb(2:2:2*N) = yL + R;
ub(1:2:2*N) = xU - R;
ub(2:2:2*N) = yU - R;
 % Random start point
x0 = up*rand(st, 2*N,1);
 dim = struct('R', R, 'xL', xL, 'xU', xU, 'yL', yL, 'yU', yU);
}%

and my object function have the form of

 f = objFcn(x, R)
which f is an integer , both x and R are vectors. where x are base station coordinates. R is their radius.

i am able to optimize the problem by using

 [x,fval,exitflag,output,lambda,grad,hessian] = ...
  fmincon(@(x) helper.objFcn(x,dimensions.R),x0,[],[],[],[],lb,ub,[],options);

and what i want to do is just optimize the problem by using ga.

Sean de Wolski 2012-8-1

This is why I suggest maybe using a 'HybridFcn'. Let ga find the valley that contains the global minimum and then use fmincon to hone in on the minimum of this valley really quickly.

Nouhaila Lazaar 2020-11-3

Hello,

I want to do the same thing, have you managed to do it? Actually, when I use ga, the program doesn't find a feasible point, I couldn't solve the problem. Can you please tell me what options I can use to solve my problem? Any suggestion will be helpful.

Thank you in advance,

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