Genetic Algorithm: Failure in initial user-supplied fitness function evaluation. GA cannot continue.

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Mauro De Francesco 2018-1-26

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/379221-genetic-algorithm-failure-in-initial-user-supplied-fitness-function-evaluation-ga-cannot-continue

评论： SARA OUANES 2019-9-25

Hello, I am recieving this king of error from genetic algorithm

    Error in
interplanetaryTrajectory>@(x)FunctionGA(x,PLANETDEP,PLANETGA,PLANETARR,mu_sun,dv_dep)
(line 28)
Fun = @(x) FunctionGA(x, PLANETDEP, PLANETGA, PLANETARR, mu_sun, dv_dep);
Error in createAnonymousFcn>@(x)fcn(x,FcnArgs{:}) (line 11)
fcn_handle = @(x) fcn(x,FcnArgs{:});
Error in fcnvectorizer (line 13)
            y(i,:) = feval(fun,(pop(i,:)));
Error in makeState (line 58)
        Score =
        fcnvectorizer(state.Population(initScoreProvided+2:end,:),FitnessFcn,1,options.SerialUserFcn);        
Error in galincon (line 17)
state = makeState(GenomeLength,FitnessFcn,Iterate,output.problemtype,options);
Error in ga (line 374)
            [x,fval,exitFlag,output,population,scores] =
            galincon(FitnessFcn,nvars, ...
Error in interplanetaryTrajectory (line 42)
[t,dv_min] = ga(Fun,nvars,A,b,[],[],LB,UB,[],[],options);
Error in FlybyMission_group_11 (line 20)
    interplanetaryTrajectory (PLANETDEP, PLANETGA, PLANETARR);
Caused by:
    Failure in user-supplied fitness function evaluation. GA cannot continue.

My code is:

    % % Function to minimize
Fun = @(x) FunctionGA(x, PLANETDEP, PLANETGA, PLANETARR, mu_sun, dv_dep);
nvars = 3; % Number of variables
LB = [T1(1) T2(1) T3(1)]; % Lower Boundaries for the variables
UB = [T1(end) T2(end) T3(end)]; % Upper Boundaries for the variables
% Linear Inequalities ( t1-t2<0 ; t2-t3<0 )
A = [ 1 -1 0; 0 1 -1]; 
b = [ 0; 0]; 
% Option set
options = optimoptions('ga','Display','off');
% Genetic Algorithm Solution
[t,dv_min] = ga(Fun,nvars,A,b,[],[],LB,UB,[],options);

I have two linear inequalities, but if I create a Constraints function that gives the exact same inequalities of the A*x < b, the code works. What am I missing?