I received an unexpected wrong result that contradict the constraint condition when using optimproblem

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昀泽
昀泽 2024-9-7
评论： 昀泽 2024-9-17
function sol = optimize_crop_allocation(A_init, P, Q, C, D, U, V, M, N, S, B_1, B_2)
% P,Q 1x41
% C,D 1x41
% U,V 54x41
% M,N 54x41
% S 1x54
% B_1,B_2 54x41
prob = optimproblem('ObjectiveSense','maximize');
A = optimvar('A', 2, 54, 41, 'Type', 'continuous', 'LowerBound', double(0));
X=A(1);
Y=A(2);
phi_f=@(X) double(0.5*min(sum(X .* M)+sum(X .* M),sum(X .* M)+C)*P'-sum(sum(X.*U)));
f_expr=fcn2optimexpr(phi_f,X);
phi_g=@(Y) double(0.5*min(sum(Y .* N)+sum(Y .* N),D+sum(Y .* N))*Q'-sum(sum(Y.*V)));
g_expr=fcn2optimexpr(phi_g,Y);
prob.Objective = f_expr+g_expr;
prob.Constraints.cons1 = sum(A(1), 2) <= S'; % the output fails to satisfy this condition
prob.Constraints.cons2 = sum(A(2), 2) <= S'; % and this
A0.A=double(A_init);
sol = solve(prob,A0);
disp(sol);
end
thanks for your help
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Torsten
Torsten 2024-9-7
编辑：Torsten 2024-9-7
As @idris said: you should experiment first with numerical matrices what you get by your summation and indexing operations. E.g. I can't believe that you want to set these constraints:
prob.Constraints.cons1 = sum(A(1), 2) <= S'; % the output fails to satisfy this condition
prob.Constraints.cons2 = sum(A(2), 2) <= S'; % and this
A(1) and A(2) are scalar values like 4 and 5. So why would it be necessary to sum over them ?
Also setting
X=A(1);
Y=A(2);
is obscure. Maybe you mean
X=A(1,:,:);
Y=A(2,:,:);
I don't know.
昀泽
昀泽 2024-9-17
Now it’s fine) the optimizer works not so well, I think, due to the non-differentiable object function min) I’ve tried other methods)

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