No feasible solution found when using quadprog

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Elisabetta Biondi
评论： Elisabetta Biondi 2021-4-7
Hello,
I am dealing with a large-scale convex quadratic programming with onlu inequality constraint.
In particular, H is a 1516-square matrix and A has dimension of 3038x1516.
I have used the code:
options = optimoptions('quadprog','interior-point-convex');
[x,fval,exitflag,output,lambda] = quadprog(H,f,A,b,[],[],[],[],[],options);
but the output is:
No feasible solution found.
quadprog stopped because it was unable to find a point that satisfies
the constraints within the default value of the constraint tolerance.
I have tried to normalize the matrix A and the vector b (as suggested in a old thread) but I got the same output. Then, using the suggestions of Converged to an Infeasible Point at https://it.mathworks.com/help/optim/ug/when-the-solver-fails.html#br44i73, I have tried to let Matlab find a feasible solution using LinProg and settingthe objective function to zero. Even in this way the solver cannot find a fesible solution. But, the vector of all zeros and of all ones are two fesible points.
Any suggestions?
Thank you a lot-
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Bruno Luong
Bruno Luong 2021-4-7
编辑：Bruno Luong 2021-4-7
Your b contain -1, so zeros is NOT feasible point either. (since A*0 is 0 vector and it is NOT <= -1)
You seem to have bug in b, or do your formulation incorrectky.
Elisabetta Biondi
Elisabetta Biondi 2021-4-7
I upload again the mat file, because actually my b has 0 as minimum

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