When I use fmincon, the optimised result does not satisfy my non liner constraints
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clear variables
close all
clc
fun = @(x)4*x(1)+x(2);
x0=[0.4,0.28]
lb = [0.01,0.01];
ub = [5,0.8];
A = [];
b = [];
Aeq = [];
beq = [];
options = optimoptions('fmincon','Algorithm','sqp');
c = @(x)(4+4*x(1)+9*x(1)^2)*(1+x(1))^2-(2*x(1)^3*x(2)+2+3*x(1)+3*x(1)^2)^2+0.001;
nonlcon = @(x)deal(c(x),[]);
[x,fval,exitflag,output] = fmincon(fun,x0,A,b,Aeq,beq,lb,ub,nonlcon,options);
exitflag
checkinitialpoint=(4+4*x0(1)+9*x0(1)^2)*(1+x0(1))^2-(2*x0(1)^3*x0(2)+2+3*x0(1)+3*x0(1)^2)^2+0.001;
checkconstraits=(4+4*x(1)+9*x(1)^2)*(1+x(1))^2-(2*x(1)^3*x(2)+2+3*x(1)+3*x(1)^2)^2+0.001;
The above is my matlab code, I input the nonlear constraints, but the results give to me is obviously not satisfy the constraints (you can see that checkconstraits is positive), my initial point is within the range.
Can anyone help me? Many thanks.
1 个评论
Torsten
2023-8-29
The solver converged to an infeasible point (see above). Your observation is the same as the exitflag from "fmincon" indicates.
回答(2 个)
Alan Weiss
2023-8-29
You would do better to use the default 'interior-point' algorithm, which arrives at a feasible solution.
fun = @(x)4*x(1)+x(2);
x0=[0.4,0.28];
lb = [0.01,0.01];
ub = [5,0.8];
A = [];
b = [];
Aeq = [];
beq = [];
% options = optimoptions('fmincon','Algorithm','sqp');
c = @(x)(4+4*x(1)+9*x(1)^2)*(1+x(1))^2-(2*x(1)^3*x(2)+2+3*x(1)+3*x(1)^2)^2+0.001;
nonlcon = @(x)deal(c(x),[]);
[x,fval,exitflag,output] = fmincon(fun,x0,A,b,Aeq,beq,lb,ub,nonlcon)
Alan Weiss
MATLAB mathematical toolbox documentation
Matt J
2023-8-29
编辑:Matt J
2023-8-29
Since it is a 2D problem, it practically begs you to pre-sweep for a good initial guess:
fun = @(x)4*x(1)+x(2);
lb = [0.01,0.01];
ub = [5,0.8];
A = [];
b = [];
Aeq = [];
beq = [];
c = @(x)(4+4*x(1)+9*x(1)^2)*(1+x(1))^2-(2*x(1)^3*x(2)+2+3*x(1)+3*x(1)^2)^2+0.001;
nonlcon = @(x)deal(c(x),[]);
[x0,fval0]=sweep(fun,c,lb,ub)
options = optimoptions('fmincon','Algorithm','sqp');
[x,fval,exitflag,output] = fmincon(fun,x0,A,b,Aeq,beq,lb,ub,nonlcon,options);
x,fval
function [x0,fval]=sweep(fun,c,lb,ub)
F=@(x1,x2) fun([x1,x2])+eps./(c([x1,x2])<=0);
[X1,X2]=ndgrid(linspace(lb(1),ub(1),30), linspace(lb(2),ub(2),30));
v=arrayfun(F,X1,X2);
[fval,i]=min(v(:));
if ~isfinite(fval)
disp 'No feasible point found'; x0=[];
else
x0=[X1(i),X2(i)];
end
end
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