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A Class of Polynomial Volumetric Barrier
Decomposition Algorithms for Stochastic Semidefinite
Programming
K. A. Ariyawansa
and Yuntao Zhu
Abstract
Ariyawansa and Zhu [5] have recently proposed a new class of optimization problems termed
stochastic semidefinite programs (SSDP's). SSDP's may be viewed as an extension of two-stage
stochastic (linear) programs with recourse (SLP's). Zhao [25] has derived a decomposition algo-
rithm for SLP's based on a logarithmic barrier and proved its polynomial complexity. Mehrotra
and ¨Ozevin [17] have extended the work of Zhao [25] to the case of SSDP's to derive a polyno-
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