We study a parallel batch-scheduling problem that involves the constraints of different job release times, non-identical job sizes, and incompatible job families, is addressed. Mixed integer programming (MIP) and constraint programming (CP) models are proposed and tested on a set of common problem instances from a paper in the literature. Then, we compare the performance of the models with that of a variable neighbourhood search (VNS) heuristic from the same paper. Computational results show that CP outperforms VNS with respect to solution quality and run time by 3.4~6.8% and 47~91%, respectively. When compared to optimal solutions, the results demonstrate CP is capable of generating a near optimal solution in a short amount of time.

Original languageEnglish (US)
JournalIEEE Transactions on Semiconductor Manufacturing
StateAccepted/In press - Aug 15 2017


  • Computational modeling
  • CP
  • Diffusion processes
  • incompatible
  • Job shop scheduling
  • MIP
  • parallel batching
  • Programming
  • Search problems
  • Single machine scheduling
  • VNS.

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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