Integrated GA and AHP for re-entrant flow shop scheduling problem

Danping Lin, Ka Man Lee, Zhang Wu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)


This paper proposes a novel way to incorporate the analytical hierarchy analysis into the genetic algorithm to solve the flow shop scheduling problem with reentrant jobs. The proposed approach allows the manufacturers take many criteria into consideration genetic algorithm gets the near-optimal sequence while the analytical hierarchy analysis assists to fulfill the multiple criteria as well as fasten the convergence that nested in the selection procedure. Initial population given by the genetic algorithm is filtered by the AHP so that the preferred chromosomes are kept as parents to generate the offspring. To demonstrate how the proposed approach works for the re-entrant flow shop scheduling, a case study of a repairing company whose jobs with dynamic re-entrant characteristic have been conducted. The experiments simulate the case scenario and the results indicate the superiority of proposed method over the practical approach. This finding is able to provide a solid foundation on which the scheduler can enhance the efficiency and accuracy of the re-entrant scheduling.
Original languageEnglish
Title of host publication2011 IEEE International Conference on Quality and Reliability, ICQR 2011
Number of pages5
Publication statusPublished - 24 Oct 2011
Externally publishedYes
Event2011 IEEE International Conference on Quality and Reliability, ICQR 2011 - Bangkok, Thailand
Duration: 14 Sep 201117 Sep 2011


Conference2011 IEEE International Conference on Quality and Reliability, ICQR 2011


  • analytical hierarchy process
  • flow shop
  • Genetic algorithm
  • multiple objectives
  • re-entrant

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

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