Compact MILP formulations for the p-center problem

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The p-center problem consists in selecting p centers among M to cover N clients, such that the maximal distance between a client and its closest selected center is minimized. For this problem we propose two new and compact integer formulations. Our first formulation is an improvement of a previous formulation. It significantly decreases the number of constraints while preserving the optimal value of the linear relaxation. Our second formulation contains less variables and constraints but it has a weaker linear relaxation bound. We besides introduce an algorithm which enables us to compute strong bounds and significantly reduce the size of our formulations. Finally, the efficiency of the algorithm and the proposed formulations are compared in terms of quality of the linear relaxation and computation time over instances from OR-Library.

Original languageEnglish
Title of host publicationCombinatorial Optimization - 5th International Symposium, ISCO 2018, Revised Selected Papers
EditorsGiovanni Rinaldi, A. Ridha Mahjoub, Jon Lee
PublisherSpringer Verlag
Pages14-25
Number of pages12
ISBN (Print)9783319961507
DOIs
Publication statusPublished - 1 Jan 2018
Event5th International Symposium on Combinatorial Optimization, ISCO 2018 - Marrakesh, Morocco
Duration: 11 Apr 201813 Apr 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10856 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Symposium on Combinatorial Optimization, ISCO 2018
Country/TerritoryMorocco
CityMarrakesh
Period11/04/1813/04/18

Keywords

  • Discrete location
  • Equivalent formulations
  • Integer programming
  • p-center

Fingerprint

Dive into the research topics of 'Compact MILP formulations for the p-center problem'. Together they form a unique fingerprint.

Cite this