The Facility Location Problem with a Joint Probabilistic Constraint

A. Suzuki*, T. Fukuba, T. Shiina

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study shows the effectiveness of the cutting plane method by applying it to the facility location problem with probabilistic constraints. Probabilistic constraints are those that should be satisfied at a certain probabilistic level and can consider the uncertainty of the parameters involved in the problem. Problems with such probabilistic constraints are generally difficult to solve. Therefore, based on previous research, we consider transforming a problem with probabilistic constraints into a 0–1 mixed integer programming problem under special conditions. Thereafter, we introduce the cutting plane method using a valid inequality of the feasible region.

Original languageEnglish
Title of host publicationIntegrated Uncertainty in Knowledge Modelling and Decision Making - 8th International Symposium, IUKM 2020, Proceedings
EditorsVan-Nam Huynh, Tomoe Entani, Chawalit Jeenanunta, Masahiro Inuiguchi, Pisal Yenradee
PublisherSpringer Science and Business Media Deutschland GmbH
Pages26-37
Number of pages12
ISBN (Print)9783030625085
DOIs
Publication statusPublished - 2020
Event8th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2020 - Phuket, Thailand
Duration: 2020 Nov 112020 Nov 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12482 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2020
Country/TerritoryThailand
CityPhuket
Period20/11/1120/11/13

Keywords

  • Cutting plane method
  • Facility location problem
  • Probabilistic constraints

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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