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

Hanyorig Choi, Shunichi Ohmori, Kazuho Yoshimoto, Hiroaki Ohtake

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルSCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems
ホスト出版物のサブタイトルLogistics Systems and Engineering
出版ステータスPublished - 2010
イベント2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering, SCMIS 2010 - Hong Kong, China
継続期間: 2010 10 62010 10 8

出版物シリーズ

名前SCMIS 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

ASJC Scopus subject areas

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

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