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Joint rectangular geometric chance constrained programs

Jia Liu (jia.liu***at***lri.fr)
Chuan Xu (chuan.xu***at***lri.fr)
Abdel Lisser(lisser***at***lri.fr)
Zhiping Chen(zchen***at***xjtu.edu.cn)

Abstract: This paper discusses joint rectangular geometric chance constrained programs. When the stochastic parameters are elliptically distributed and pairwise independent, we present a reformulation of the joint rectangular geometric chance constrained programs. As the reformulation is not convex, we propose new convex approximations based on variable transformation together with piecewise linear approximation method. Our results show that the approximations are tight.

Keywords: Geometric optimization, Joint probabilistic constraint, Variable transformation, Piecewise linear approximation

Category 1: Stochastic Programming


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Entry Submitted: 10/28/2016
Entry Accepted: 10/30/2016
Entry Last Modified: 10/28/2016

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