Scheduling job families on non-identical parallel machines with time constraints

Ali Obeid (), Stéphane Dauzère-Pérès () and Claude Yugma ()

Annals of Operations Research, 2014, vol. 213, issue 1, 234 pages

Abstract: This paper studies the scheduling of lots (jobs) of different product types (job family) on parallel machines, where not all machines are able to process all job families (non-identical machines). A special time constraint, associated to each job family, should be satisfied for a machine to remain qualified for processing a job family. This constraint imposes that the time between the executions of two consecutive jobs of the same family on a qualified machine must not exceed the time threshold of the family. Otherwise, the machine becomes disqualified. This problem comes from semiconductor manufacturing, when Advanced Process Control constraints are considered in scheduling problems. To solve this problem, two Mixed Integer Linear Programming models are proposed that use different types of variables. Numerical experiments show that the second model is much more effective, and that there is a trade-off between optimizing the scheduling objective and maximizing the number of machines that remain qualified for the job families. Two heuristics are also presented and studied in the numerical experiments. Copyright Springer Science+Business Media, LLC 2014

Keywords: Scheduling; Parallel machines; Time constraint; Mixed integer linear programming; Heuristics; Semiconductor manufacturing (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10479-012-1107-4

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