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Solving a chemical batch scheduling problem by local search

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  • Peter Brucker
  • Johann Hurink

Abstract

In this paper the following chemical batch scheduling problem is considered: a set of orders has to be processed on a set of facilities. For each order a given amount of a product must be produced by means of chemical reactions before a given deadline. The production consists of a sequence of processes whereby each process has to be performed by one facility out of a given subset of facilities allowed for this process. The processing times depend on the choice of the facility and the processing is done in batch mode with given minimum and maximum sizes. The problem is to assign the processes to the facilities, splitting them into batches, and scheduling these batches in order to produce the demands within the given deadlines. For the scheduling part of the problem we present an approach based on the following steps. First, a procedure to calculate the minimum number of batches needed to satisfy the demands is presented. Based on this, the given problem is modeled in two different ways: as a general shop scheduling problem with set-up times or as scheduling problem with positive time-lags. Finally, a two-phase tabu search method is presented which is based on the two different formulations of the problem. The method is tested on some real world data. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Peter Brucker & Johann Hurink, 2000. "Solving a chemical batch scheduling problem by local search," Annals of Operations Research, Springer, vol. 96(1), pages 17-38, November.
    • Handle: RePEc:spr:annopr:v:96:y:2000:i:1:p:17-38:10.1023/a:1018959704264
    DOI: 10.1023/A:1018959704264
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    Cited by:

    1. Huang, Wei & Chen, Bo, 2007. "Scheduling of batch plants: Constraint-based approach and performance investigation," International Journal of Production Economics, Elsevier, vol. 105(2), pages 425-444, February.
    2. Wang, Haibo & Alidaee, Bahram, 2019. "Effective heuristic for large-scale unrelated parallel machines scheduling problems," Omega, Elsevier, vol. 83(C), pages 261-274.

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