New reformulations for probabilistically constrained quadratic programs

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

2 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)550-556
Journal / PublicationEuropean Journal of Operational Research
Volume233
Issue number3
Online published8 Sep 2013
Publication statusPublished - 16 Mar 2014
Externally publishedYes

Abstract

The mixed integer quadratic programming (MIQP) reformulation by Zheng, Sun, Li, and Cui (2012) for probabilistically constrained quadratic programs (PCQP) recently published in EJOR significantly dominates the standard MIQP formulation (Ruszczynski, 2002; Benati & Rizzi, 2007) which has been widely adopted in the literature. Stimulated by the dimensionality problem which Zheng et al. (2012) acknowledge themselves for their reformulations, we study further the characteristics of PCQP and develop new MIQP reformulations for PCQP with fewer variables and constraints. The results from numerical tests demonstrate that our reformulations clearly outperform the state-of-the-art MIQP in Zheng et al. (2012).

Research Area(s)

  • Mixed-integer quadratic program, Probabilistic constraint, Quadratic programming, Semi-definite programming, Value-at-risk/variance portfolio selection