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Quadratic optimization with quadratic constraints

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Rene
Rene 2012 年 2 月 1 日
コメント済み: Matt J 2020 年 9 月 18 日
Hi everyone,
I have an optimization problem with a quadratic objective function and quadratic constraint functions AND the problem is non-convex.
Is there any Matlab function which can do this? QUADPROG and FMINCON only allow linear constraints afaik. I also tried a solver by MOSEK (<http://mosek.com/>) but this only can deal with convex problems. Is there any tool/function for the non-convex case?
Thanks! René

採用された回答

Steve Grikschat
Steve Grikschat 2012 年 2 月 1 日
Hi Rene (sorry, can't get the accent right)
You can use FMINCON to solve this problem. However, there is no dedicated input for quadratic constraints. Instead, you must formulate them as nonlinear constraints.
Since your problem is non-convex, you should probably use the interior-point algorithm. http://www.mathworks.com/help/toolbox/optim/ug/brnoxzl.html#brnpd5f
Also, since your objective and constraint functions are quadratic, you can save a lot of time by providing outputs that compute the gradients (H*x + f) and a function that computes the Hessian (of the Lagrangian, in this case).
To do this, you'll need to create functions to compute your objective and constraints, as well as setting these options:
- Algorithm to 'interior-point' - GradObj to 'on' (user-computed 1st derivatives) - GradConstr to 'on' (same) - Hessian to 'user-supplied' (user-computed 2nd derivatives) - HessFcn to a handle to a function that computes the Hessian of the Lagrangian (see this page:http://www.mathworks.com/help/toolbox/optim/ug/fmincon.html#f186882)
+Steve
  1 件のコメント
Matt J
Matt J 2020 年 9 月 18 日
Rene commented:
Sorry for responding that late, I had been busy with other stuff lately and just wanted to say "thank you" for your help, Steve!

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その他の回答 (2 件)

Matt J
Matt J 2016 年 6 月 19 日
If you have single, L2-norm constraint, then this FEX submission should help,

Steve Grikschat
Steve Grikschat 2020 年 9 月 18 日
As of R2020b, Optimization Toolbox now has a dedicated solver for second-order cone programming, which can be used to solve quadratic constrained problems.
https://www.mathworks.com/help//optim/ug/convert-qp-to-socp.html
Function reference:
coupled with a function to make a second-order cone constraint
For an example see

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