Polyhedral approximations in p-order cone programming

Alexander Vinel, Pavlo A. Krokhmal

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

This paper discusses the use of polyhedral approximations in solving p-order cone programming (pOCP) problems, or linear problems with p-order cone constraints, and their mixed-integer extensions. In particular, it is shown that the cutting-plane technique proposed in Krokhmal and Soberanis [Risk optimization with p-order conic constraints: A linear programming approach, Eur. J. Oper. Res. 201 (2010), pp. 653-671, http://dx.doi.org/10.1016/j.ejor.2009. 03.053] for a special type of polyhedral approximations of pOCP problems, which allows for generation of cuts in constant time not dependent on the accuracy of approximation, is applicable to a larger family of polyhedral approximations. We also show that it can further be extended to form an exact solution method for pOCP problems with O(ε-1) iteration complexity. Moreover, it is demonstrated that an analogous constant-time cut-generating algorithm exists for recursively constructed lifted polyhedral approximations of second-order cones due to Ben-Tal and Nemirovski [On polyhedral approximations of the second-order cone, Math. Oper. Res. 26 (2001), pp. 193-205. Available at http://dx.doi.org/ 10.1287/moor.26.2.193.10561]. It is also shown that the developed polyhedral approximations and the corresponding cutting-plane solution methods can be efficiently used for obtaining exact solutions of mixed-integer pOCP problems.

Original languageEnglish (US)
Pages (from-to)1210-1237
Number of pages28
JournalOptimization Methods and Software
Volume29
Issue number6
DOIs
StatePublished - Nov 2 2014
Externally publishedYes

Keywords

  • cutting-plane methods
  • mixed-integer p-order cone programming
  • p-order cone programming
  • polyhedral approximation
  • portfolio optimization
  • second-order cone programming
  • stochastic programming

ASJC Scopus subject areas

  • Software
  • Control and Optimization
  • Applied Mathematics

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