Two-Stage Stochastic Semidefinite Programming and Decomposition Based Interior Point Methods: Theory
نویسندگان
چکیده
We introduce two-stage stochastic semidefinite programs with recourse and present a Benders decomposition based linearly convergent interior point algorithms to solve them. This extends the results in Zhao [16] wherein it was shown that the logarithmic barrier associated with the recourse function of two-stage stochastic linear programs with recourse behaves as a strongly self-concordant barrier on the first stage solutions. In this paper we develop the necessary theory. A companion paper [8] addresses implementation issues for the theoretical algorithms of this paper.
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