Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach

Tung Sun Chan, Sai Ho Chung, L. Y. Chan, G. Finke, M. K. Tiwari

Research output: Journal article publicationJournal articleAcademic researchpeer-review

110 Citations (Scopus)

Abstract

In general, distributed scheduling problem focuses on simultaneously solving two issues: (i) allocation of jobs to suitable factories and (ii) determination of the corresponding production scheduling in each factory. The objective of this approach is to maximize the system efficiency by finding an optimal planning for a better collaboration among various processes. This makes distributed scheduling problems more complicated than classical production scheduling ones. With the addition of alternative production routing, the problems are even more complicated. Conventionally, machines are usually assumed to be available without interruption during the production scheduling. Maintenance is not considered. However, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it influences the production scheduling. In this connection, maintenance should be considered in distributed scheduling. The objective of this paper is to propose a genetic algorithm with dominant genes (GADG) approach to deal with distributed flexible manufacturing system (FMS) scheduling problems subject to machine maintenance constraint. The optimization performance of the proposed GADG will be compared with other existing approaches, such as simple genetic algorithms to demonstrate its reliability. The significance and benefits of considering maintenance in distributed scheduling will also be demonstrated by simulation runs on a sample problem.
Original languageEnglish
Pages (from-to)493-504
Number of pages12
JournalRobotics and Computer-Integrated Manufacturing
Volume22
Issue number5-6
DOIs
Publication statusPublished - 1 Oct 2006
Externally publishedYes

Keywords

  • Distributed scheduling
  • Flexible manufacturing systems
  • Genetic algorithms
  • Maintenance

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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