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Quadratic optimization with quadratic constraints

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Rene 2012년 2월 1일
댓글: Matt J 2020년 9월 18일
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 (<>) but this only can deal with convex problems. Is there any tool/function for the non-convex case?
Thanks! René

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Steve Grikschat
Steve Grikschat 2012년 2월 1일
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.
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:
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Matt J
Matt J 2020년 9월 18일
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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Steve Grikschat
Steve Grikschat 2020년 9월 18일
As of R2020b, Optimization Toolbox now has a dedicated solver for second-order cone programming, which can be used to solve quadratic constrained problems.
Function reference:
coupled with a function to make a second-order cone constraint
For an example see

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