Continuous Reformulation of Binary Variables, Revisited

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Abstract

We discuss a class of tightly feasible MILP for which branch-and-bound is ineffective. We consider its hardness, evaluate the probability that randomly generated instances are feasible, and introduce a heuristic solution method based on the old idea of reformulating binary variables to continuous while introducing a linear complementarity constraint. We show the extent of the computational advantage, under a time limit, of our heuristic with respect to a state-of-the-art branch-and-bound implementation.

Original languageEnglish
Title of host publicationMathematical Optimization Theory and Operations Research
Subtitle of host publicationRecent Trends - 20th International Conference, MOTOR 2021, Revised Selected Papers
EditorsAlexander Strekalovsky, Yury Kochetov, Tatiana Gruzdeva, Andrei Orlov
PublisherSpringer Science and Business Media Deutschland GmbH
Pages201-215
Number of pages15
ISBN (Print)9783030864323
DOIs
Publication statusPublished - 1 Jan 2021
Event20th International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2021 - Virtual, Online
Duration: 5 Jul 202110 Jul 2021

Publication series

NameCommunications in Computer and Information Science
Volume1476 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference20th International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2021
CityVirtual, Online
Period5/07/2110/07/21

Keywords

  • Hard instances
  • Infeasible
  • Market share
  • Market split
  • Reformulation

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