Fuzzy job shop scheduling problem with availability constraints

  • Authors:
  • Deming Lei

  • Affiliations:
  • School of Automation, Wuhan University of Technology, 122 Luoshi Road, Wuhan, Hubei Province, People's Republic of China

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2010

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Abstract

This paper presents the fuzzy job shop scheduling problem with availability constraints. The objective is to find a schedule that maximizes the minimum agreement index subject to periodic maintenance, non-resumable jobs and fuzzy due-date. A random key genetic algorithm (RKGA) is proposed for the problem, in which a novel random key representation, a new decoding strategy incorporating maintenance operation and discrete crossover (DX) are used. RKGA is applied to some fuzzy scheduling problem with availability constraints and compared with other algorithms. Computational results show that RKGA performs better than other algorithms.