I need help for optimization using Ga

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noura 2024-8-19

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评论： Star Strider 2024-8-19

I want to make optimization using genetic algorithm to minimize error between force and displacement (simulated and desired ) . I have 3 numbers of variables (height , depth , width) .. can anyone help me for the coding please

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noura 2024-8-19

Messenger_creation_58bdd1d5-44b2-4fb8-9048-c9b4ef71aba6.jpeg

I need to make optimization using ga to minimize the error between simulated and desired chart as mentioned. The parameters ( height , depth , width ) of a cuboid

Sam Chak 2024-8-19

Since you already have the code to run the sim, getting the "Simulated Displacement" points and the "Desired Displacement" points into the "data" array in @Walter Roberson's code should be a relatively easy thing to do.

Since the cuboid's dimension cannot be zero or infinity, estimate some realistic values for the lower and upper bounds for the GA to search within these bounded regions.

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Answer 1

Walter Roberson 2024-8-19

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https://ww2.mathworks.cn/matlabcentral/answers/2146194-i-need-help-for-optimization-using-ga#answer_1500764

在 MATLAB Online 中打开

data = Something Appropriate to set up data
numvar = 3;
A = []; b = [];
Aeq = []; beq = [];
lb = [0, 0, 0];
ub = [inf, inf, inf];
best = ga(@(x)Simulate_force(x, data), numvar, A, b, Aeq, beq, lb, ub);
function val = Simulate_force(x, data)
   force = something appropriate using data
   displacement = something else appropriate using data
   val = sum((force - displacement).^2);
end

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Answer 2

Star Strider 2024-8-19

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https://ww2.mathworks.cn/matlabcentral/answers/2146194-i-need-help-for-optimization-using-ga#answer_1500924

在 MATLAB Online 中打开

Messenger_creation_58bdd1d5-44b2-4fb8-9048-c9b4ef71aba6.jpeg

Perhaps something like this —

figure

imshow(imread('Messenger_crea...ef71aba6.jpeg'))

x = [1 2.5 10:10:100];

simulated = 0.007 * x;

desired = 0.021 * x;

objfcn = @(b,x) b(1) + b(2).*x; % Objective Function

ftns = @(b) norm(desired - objfcn(b,simulated)); % Fitness Function

% PopSz = 500;

% Parms = 2;

% optsAns = optimoptions('ga', 'PopulationSize',PopSz, 'InitialPopulationMatrix',randi(1E+4,PopSz,Parms)*1E-3, 'MaxGenerations',5E3, 'FunctionTolerance',1E-10); % Options Structure For 'Answers' Problems

% t0 = clock;

% fprintf('\nStart Time: %4d-%02d-%02d %02d:%02d:%07.4f\n', t0)

% [B,fval,exitflag,output,population,scores] = ga(ftns, Parms, [],[],[],[],zeros(Parms,1),Inf(Parms,1),[],[],optsAns);

% t1 = clock;

% fprintf('\nStop Time: %4d-%02d-%02d %02d:%02d:%07.4f\n', t1)

% GA_Time = etime(t1,t0)

% DT_GA_Time = datetime([0 0 0 0 0 GA_Time], 'Format','HH:mm:ss.SSS');

% fprintf('\nElapsed Time: %23.15E\t\t%s\n\n', GA_Time, DT_GA_Time)

%

% fprintf('Fitness value at convergence = %.4f\nGenerations \t\t\t\t = %d\n\n',fval,output.generations)

%

% fprintf(1,'\tRate Constants:\n')

% for k1 = 1:length(B)

% fprintf(1, '\t\tB(%2d) = %8.5f\n', k1, theta(k1))

% end

B = ga(ftns, 2)

ga stopped because the average change in the fitness value is less than options.FunctionTolerance.

B = 1x2

0.0106 2.9520

figure

plot(x, simulated, 'o-', 'DisplayName','Simulated Displacement')

hold on

plot(x, desired, 'x-', 'DisplayName','Desired Displacement')

plot(x, objfcn(B, simulated), 'sr-', 'DisplayName','Optimised Result')

hold off

grid

legend('Location','best')

The ‘B’ vector here are the intercept and slope transformation required to transform ‘simulated’ to ‘desired’. Using ga may be a bit of ‘overkill’ for this problem, however it can be done, assuming I understand what you want to do.

(I’m getting some sort of weird error with respect to declaring the options structure, so I commented-out that code example. That error is ‘The 'ga' function requires the Global Optimization Toolbox’ so I ran it without the options structure and the code I usually use for ga problems, and it worked.)

.

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Sam Chak 2024-8-19

For static optimization problems involving linear graphs, using a ga() may indeed be considered excessive. However, it appears that the OP intends to determine the dimensions of a cuboid (length × width × height) such that, when a certain magnitude of force F is applied, the cuboid of mass m is displaced by a specific distance x. While the 2nd-order motion model is certainly available, the OP has not provided it.