Abstract

In this paper, we discuss a flexible flow shop scheduling problem with batch processing machines at each stage and with jobs that have unequal ready times. Scheduling problems of this type can be found in semiconductor wafer fabrication facilities (wafer fabs). We are interested in minimizing the total weighted tardiness of the jobs. We present a mixed integer programming formulation. The batch scheduling problem is NP-hard. Therefore, an iterative stage-based decomposition approach is proposed that is hybridized with neighborhood search techniques. The decomposition scheme provides internal due dates and ready times for the jobs on the first and second stage, respectively. Each of the resulting parallel machine batch scheduling problems is solved by variable neighborhood search in each iteration. Based on the schedules of the subproblems, the internal due dates and ready times are updated. We present the results of designed computational experiments that also consider the number of machines assigned to each stage as a design factor. It turns out that the proposed hybrid approach outperforms an iterative decomposition scheme where a fairly simple heuristic based on time window decomposition and the apparent tardiness cost dispatching rule is used to solve the subproblems. Recommendations for the design of the two stages with respect to the number of parallel machines on each stage are given.

Original languageEnglish (US)
Pages (from-to)1-18
Number of pages18
JournalJournal of Scheduling
DOIs
StateAccepted/In press - Jun 13 2017

Keywords

  • Batching
  • Computational experiments
  • Decomposition
  • Two-stage flexible flow shop
  • Variable neighborhood search

ASJC Scopus subject areas

  • Software
  • Engineering(all)
  • Management Science and Operations Research
  • Artificial Intelligence

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