Particle swarm optimization for multi-function worker assignment problem

Shamshul Bahar Yaakob, Junzo Watada

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

3 Citations (Scopus)

Abstract

A problem of worker assignment in cellular manufacturing (CM) environment is studied in this paper. The worker assignment problem is an NP-complete problem. In this paper, worker assignment method is modeled based on the principles of particle swarm optimization (PSO). PSO applies a collaborative population-based search, which models over the social behavior of fish schooling and bird flocking. PSO system combines local search method through self-experience with global search methods through neighboring experience, attempting to balance the exploration-exploitation trade-off which determines the efficiency and accuracy of an optimization. An effect of velocity controlled for the PSO's is newly included in this paper. We applied the adaptation and implementation of the PSO search strategy to the worker assignment problem. Typical application examples are also presented: the results demonstrate that the velocity information is an important factor for searching best solution and our method is a viable approach for the worker assignment problem.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages203-211
Number of pages9
Volume5712 LNAI
EditionPART 2
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009 - Santiago
Duration: 2009 Sep 282009 Sep 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5712 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009
CitySantiago
Period09/9/2809/9/30

Fingerprint

Assignment Problem
Particle swarm optimization (PSO)
Particle Swarm Optimization
Search Methods
Assignment
Cellular Manufacturing
Flocking
Social Behavior
Global Search
Search Strategy
Fish
Cellular manufacturing
Exploitation
Local Search
Birds
NP-complete problem
Trade-offs
Computational complexity
Optimization
Demonstrate

Keywords

  • Cellular manufacturing
  • Particle swarm optimization
  • Worker assignment

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Yaakob, S. B., & Watada, J. (2009). Particle swarm optimization for multi-function worker assignment problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 5712 LNAI, pp. 203-211). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5712 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-04592-9_26

Particle swarm optimization for multi-function worker assignment problem. / Yaakob, Shamshul Bahar; Watada, Junzo.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5712 LNAI PART 2. ed. 2009. p. 203-211 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5712 LNAI, No. PART 2).

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

Yaakob, SB & Watada, J 2009, Particle swarm optimization for multi-function worker assignment problem. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 edn, vol. 5712 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5712 LNAI, pp. 203-211, 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009, Santiago, 09/9/28. https://doi.org/10.1007/978-3-642-04592-9_26
Yaakob SB, Watada J. Particle swarm optimization for multi-function worker assignment problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 ed. Vol. 5712 LNAI. 2009. p. 203-211. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-642-04592-9_26
Yaakob, Shamshul Bahar ; Watada, Junzo. / Particle swarm optimization for multi-function worker assignment problem. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5712 LNAI PART 2. ed. 2009. pp. 203-211 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
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