A genetic algorithms simulation approach for the multi-attribute combinatorial dispatching decision problem

Taho Yang, Yiyo Kuo, Chiwoon Cho

Research output: Contribution to journalArticlepeer-review

58 Citations (Scopus)

Abstract

This paper presents a genetic algorithms (GA) simulation approach in solving a multi-attribute combinatorial dispatching (MACD) decision problem in a flow shop with multiple processors (FSMP) environment. The simulation is capable of modeling a non-linear and stochastic problem. GA are one of the commonly used metaheuristics and are a proven tool for solving complex optimization problems. The proposed GA simulation approach addresses a complex MACD problem. Its solution quality is illustrated by a case study from a multi-layer ceramic capacitor (MLCC) manufacturing plant. Because GA search results are often sensitive to the search parameters, this research optimized the GA parameters by using regression analysis. Empirical results showed that the GA simulation approach outperformed several commonly used dispatching rules. The improvements are ranging from 33% to 61%. On the other hand, the increased shop-floor-control complexity may hinder the implementation of the system. Finally, future research directions are discussed.

Original languageEnglish
Pages (from-to)1859-1873
Number of pages15
JournalEuropean Journal of Operational Research
Volume176
Issue number3
DOIs
Publication statusPublished - 2007 Feb 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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