New reformulations for probabilistically constrained quadratic programs

Yong Hsia, Baiyi Wu, Duan Li*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

2 Citations (Scopus)

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).
Original languageEnglish
Pages (from-to)550-556
JournalEuropean Journal of Operational Research
Volume233
Issue number3
Online published8 Sept 2013
DOIs
Publication statusPublished - 16 Mar 2014
Externally publishedYes

Research Keywords

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

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