Solving tri-level programming problems using a particle swarm optimization algorithm

Jialin Han, Guangquan Zhang, Yaoguang Hu, Jie Lu

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

11 Citations (Scopus)

Abstract

Tri-level programming, a special case of multilevel programming, arises to deal with decentralized decision-making problems that feature interacting decision entities distributed throughout three hierarchical levels. As tri-level programming problems are strongly NP-hard and the existing solution approaches lack universality in solving such problems, the purpose of this study is to propose an intelligence-based heuristic algorithm to solve tri-level programming problems involving linear and nonlinear versions. In this paper, we first propose a general tri-level programming problem and discuss related theoretical properties. A particle swarm optimization (PSO) algorithm is then developed to solve the tri-level programming problem. Lastly, a numerical example is adopted to illustrate the effectiveness of the proposed PSO algorithm.

Original languageEnglish
Title of host publicationProceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages569-574
Number of pages6
ISBN (Electronic)9781467373173
DOIs
Publication statusPublished - 20 Nov 2015
Event10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 - Auckland, New Zealand
Duration: 15 Jun 201517 Jun 2015

Publication series

NameProceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015

Conference

Conference10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
Country/TerritoryNew Zealand
CityAuckland
Period15/06/1517/06/15

Keywords

  • Kuhn-Tucker conditions
  • bi-level programming
  • computational intelligence
  • particle swarm optimization
  • tri-level programming

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