Quadratic optimization with quadratic constraints
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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
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Matt J
2016-6-19
0 个投票
If you have single, L2-norm constraint, then this FEX submission should help,
Steve Grikschat
2020-9-18
0 个投票
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
5 个评论
rui liu
2024-6-7
Hello, I have seen how to convert qp to socp(https://ww2.mathworks.cn/help/optim/ug/convert-qp-to-socp.html), however, I have some questions about the derivation process. So I want to ask if there are more documents about it, such as papers.
Steve Grikschat
2024-6-7
Hi,
This equivalence seems to be stated quite often,but rarely with a thorough explanation. At least, none that I could find. (For example, this paper).
rui liu
2024-6-10
thank you very much!
rui liu
2024-7-6
Hello, if there is some methods to accelerate the SOCP computation. I try to generate C code but it says "Function 'secondordercone' not supported for code generation. if there is other methods to make the solver process quick. Thank you!
Steve Grikschat
2024-7-6
C code generation for coneprog is not supported in the current release, but is on our plans (see if you can access the R2024b pre-release notes which mentions this: https://www.mathworks.com/help/releases/R2024b/optim/release-notes.html)
In the meantime, an option that can have a notable effect on the solve time is the LinearSolver option
If your linear or cone constraints are dense (many nonzeros) or have dense columns, then tuning this option may be helpful.
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