The facility location problem with probabilistic constraints

Atsuya Suzuki, Tomoki Fukuba, Takayuki Shiina

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 publication2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728197326
DOIs
Publication statusPublished - 2020 Dec 5
EventJoint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020 - Virtual, Tokyo, Japan
Duration: 2020 Dec 52020 Dec 8

Publication series

Name2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020

Conference

ConferenceJoint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2020
Country/TerritoryJapan
CityVirtual, Tokyo
Period20/12/520/12/8

Keywords

  • Cutting plane method
  • Facility location problem
  • Probabilistic constraints

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software
  • Computational Mathematics

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