Improvement of particle swarm optimization application of the mutation concept for the escape from local minima

Hanyorig Choi, Shunichi Ohmori, Kazuho Yoshimoto, Hiroaki Ohtake

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

4 Citations (Scopus)

Abstract

In this paper, the improvement of Particle Swam Optimization (PSO) is proposed. PSO is one of the evolutionary computation methods to obtain the approximate optimal solution for the continuous optimization problem with multi-peak objective function. It can be applied to solve many optimization problems arising in the Supply Chain Management, such as Facility Location Problem, Inventory Portfolio Problem or Dynamical Lot Sizing Problem. One of the major weaknesses of PSO is trapped into local optima. To overcome this weakness, in this paper, the introduction of concept of mutation in Genetic Algorithm (GA) to PSO is proposed. In the computational experiment, the three benchmark problems are tested in order to validate the effectiveness of proposed method.

Original languageEnglish
Title of host publicationSCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems
Subtitle of host publicationLogistics Systems and Engineering
Publication statusPublished - 2010 Dec 1
Event2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering, SCMIS 2010 - Hong Kong, China
Duration: 2010 Oct 62010 Oct 8

Publication series

NameSCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering

Conference

Conference2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering, SCMIS 2010
CountryChina
CityHong Kong
Period10/10/610/10/8

Keywords

  • Component
  • Genetic algorithm(ga)
  • Mutation
  • Particle swarm optimimtion(pso)
  • Stability analysis(sa)
  • Supply chain mnagement(scm)

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management

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  • Cite this

    Choi, H., Ohmori, S., Yoshimoto, K., & Ohtake, H. (2010). Improvement of particle swarm optimization application of the mutation concept for the escape from local minima. In SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering [5681798] (SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering).