Sedumi for semidefinite optimization

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The discussion centers on creating a function using SeDuMi for solving semidefinite optimization problems. It highlights the distinction between Second Order Cone Programming (SOCP) and Semidefinite Quadratic Linear Programming (SDP), noting that K.s represents semidefinite constraints while K.q is used for SOCP cones. The data organization for SOCP cones is mentioned, indicating that they are stacked above the vectorized data for SDPs. For those unfamiliar with the technical details, it is suggested to use a modeling language like YALMIP, which simplifies the process without requiring in-depth knowledge of SeDuMi's intricacies.
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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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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.
 
Thanks!
 
whoa :) is this lofberg himself?
 
I strongly believe I am me.

trambolin said:
whoa :) is this lofberg himself?
 

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