Sedumi for semidefinite optimization

In summary, the conversation discusses the use of the sedumi function for solving semidefinite optimization problems. It also mentions the use of K.s and K.q for semidefinite constraints and Second order cone programming, respectively. The speaker suggests using a modelling language like YALMIP instead of worrying about these details in SeDuMi.
  • #1
dsprao
8
0
Dear Friends,

Some one can help me to make sedumi function which can solve the semidefinite optimization. Additionally, how can I distinguish between Second order cone programming and semidefinite quadratic linear programming.

Thank You.
 
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  • #2
K.s is used for semidefinite constraints and K.q are used for the SOCP cones. The data for the SOCP cones are stacked above the vectorized data for the SDPs.

If this sounds like jibberish to you, use a modelling language instead, such as YALMIP, and you don't have to think about these details in SeDuMi.

dsprao said:
Dear Friends,

Some one can help me to make sedumi function which can solve the semidefinite optimization. Additionally, how can I distinguish between Second order cone programming and semidefinite quadratic linear programming.

Thank You.
 
  • #3
Thanks!
 
  • #4
whoa :) is this lofberg himself?
 
  • #5
I strongly believe I am me.

trambolin said:
whoa :) is this lofberg himself?
 

Related to Sedumi for semidefinite optimization

1. What is Sedumi for semidefinite optimization?

Sedumi is a software package that is used for solving semidefinite optimization problems. It is based on the primal-dual interior point method and is designed specifically for large-scale problems.

2. How does Sedumi work?

Sedumi works by converting the semidefinite optimization problem into a standard form, which can then be solved using the primal-dual interior point method. It uses matrix factorization and iterative techniques to find the optimal solution.

3. What types of problems can Sedumi solve?

Sedumi can solve a wide range of semidefinite optimization problems, including linear matrix inequalities, second-order cone programs, and semidefinite programs. It can also handle problems with complex variables and nonlinear functions.

4. Is Sedumi easy to use?

Sedumi has a user-friendly interface and can be easily implemented using MATLAB or Octave. However, it requires a basic understanding of semidefinite optimization and linear algebra in order to properly formulate and solve the problem.

5. Are there any limitations to Sedumi?

While Sedumi is a powerful tool for solving semidefinite optimization problems, it does have some limitations. It may not be suitable for problems with a large number of variables or constraints, and may not converge for highly ill-conditioned problems.

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