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

Hanyorig Choi; Shunichi Ohmori; Kazuho Yoshimoto; Hiroaki Ohtake

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

Hanyorig Choi^*, Shunichi Ohmori, Kazuho Yoshimoto, Hiroaki Ohtake

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 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 language	English
Title of host publication	SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems
Subtitle of host publication	Logistics Systems and Engineering
Publication status	Published - 2010
Event	2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering, SCMIS 2010 - Hong Kong, China Duration: 2010 Oct 6 → 2010 Oct 8

Publication series

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

Conference

Conference	2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering, SCMIS 2010
Country/Territory	China
City	Hong Kong
Period	10/10/6 → 10/10/8

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

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 Article 5681798 (SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering).

Improvement of particle swarm optimization application of the mutation concept for the escape from local minima. / Choi, Hanyorig; Ohmori, Shunichi; Yoshimoto, Kazuho et al.
SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering. 2010. 5681798 (SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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, 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering, SCMIS 2010, Hong Kong, China, 10/10/6.

Choi H, Ohmori S, Yoshimoto K, Ohtake H. 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. 2010. 5681798. (SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering).

Choi, Hanyorig ; Ohmori, Shunichi ; Yoshimoto, Kazuho et al. / Improvement of particle swarm optimization application of the mutation concept for the escape from local minima. SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering. 2010. (SCMIS 2010 - Proceedings of 2010 8th International Conference on Supply Chain Management and Information Systems: Logistics Systems and Engineering).

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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.",

keywords = "Component, Genetic algorithm(ga), Mutation, Particle swarm optimimtion(pso), Stability analysis(sa), Supply chain mnagement(scm)",

author = "Hanyorig Choi and Shunichi Ohmori and Kazuho Yoshimoto and Hiroaki Ohtake",

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AB - 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.

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

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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