How do I help quadprog converge?

5 次查看(过去 30 天)
Leigh Sneddon
Leigh Sneddon 2019-8-15
编辑: Matt J 2019-8-16
Quadprog quits with exitFlag = -2, and the message below. How do I help it converge to a feasible point?
"quadprog optimization failed: Converged to an infeasible point.
quadprog stopped because the size of the current step is less than the default value of the step size tolerance but constraints are not satisfied to within the selected value of the constraint tolerance.
Stopping criteria details:
Optimization stopped because the relative changes in all elements of x are less than options.StepTolerance = 1.000000e-12, but the relative maximum constraint violation, 1.902013e-14, exceeds options.ConstraintTolerance = 1.000000e-06.
Optimization Metric Options
max(abs(delta_x./x)) = 1.82e-13 StepTolerance = 1e-12 (default)
relative max(constraint violation) = 1.90e-14 ConstraintTolerance = 1e-06 (selected)"
  9 个评论
Walter Roberson
Walter Roberson 2019-8-15
I cannot find the information on the problem that came to mind; unfortunately the bug reports are now difficult to search :(

请先登录,再进行评论。

回答(1 个)

Matt J
Matt J 2019-8-15
编辑:Matt J 2019-8-15
Is checking that the constraints are satisfied and the optimality measure is low a good rule of thumb for making this decision?
Checking the first order KKT conditions would be the best test, assuming your quadratic is convex. The final output argument of quadprog gives the solver's idea of the optimal Lagrange multipliers,
[x,fval,exitflag,output,lambda] = quadprog(___)
But I would first recommend upgrading to a Matlab version that doesn't have this bug.
  2 个评论
Leigh Sneddon
Leigh Sneddon 2019-8-16
Optimizer precision limitations will mean that none of the conditions is satisfied exactly. Is there a way of knowing, given the tolerances used, how much mismatch is consistent with a correct solution?
Matt J
Matt J 2019-8-16
编辑:Matt J 2019-8-16
What does "consistent with a correct solution" mean to you? Even if quadprog's exit message had been a proper one, what is the deviation distance from the true optimum that your application can tolerate, and how would you have known that the result is within that distance if quadprog had behaved normally?

请先登录,再进行评论。

类别

Help CenterFile Exchange 中查找有关 Quadratic Programming and Cone Programming 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by