A competitive neural network approach to multi-objective FMS scheduling

H. S. Min, Y. Yih, C. O. Kim

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

The main contribution of this paper is the development of a multi-objective FMS scheduler which is designed to maximally satisfy the desired values of multiple objectives set by the operator. For each production interval, a decision rule for each decision variable is chosen by the FMS scheduler. A competitive neural network is applied to present fast but good decision rules to the operator. A unique feature of the FMS scheduler is that the competitive neural network generates the next decision rules based on the current decision rules, system status and performance measures. A commercial FMS is simulated to prove the effectiveness of the FMS scheduler. The result shows that the FMS scheduler can successfully satisfy multiple objectives.

Original languageEnglish
Pages (from-to)1749-1765
Number of pages17
JournalInternational Journal of Production Research
Volume36
Issue number7
DOIs
Publication statusPublished - 1998 Jan 1

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Scheduling
Neural networks
Decision rules
Multiple objectives
Operator

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Cite this

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A competitive neural network approach to multi-objective FMS scheduling. / Min, H. S.; Yih, Y.; Kim, C. O.

In: International Journal of Production Research, Vol. 36, No. 7, 01.01.1998, p. 1749-1765.

Research output: Contribution to journalArticle

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