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Computing lower and upper bounds for a large-scale industrial job shop scheduling problem

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  • Drótos, Márton
  • Erdos, Gábor
  • Kis, Tamás

Abstract

In this paper we present a case study from the lighting industry concerned with the scheduling of a set of job families each representing the production of a particular end-item in a given quantity. It is a job shop type problem, where each job family has a number of routing alternatives, and the solution has to respect batching and machine availability constraints. All jobs of the same job family have a common release date and a common due date, and they differ only in size. The objective is to minimize the total tardiness of the job families, rather than that of individual jobs. We propose a two-phase method based on solving a mixed-integer linear program and then improving the initial solution by tabu search. We evaluate our method on real-world as well as generated instances.

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  • Drótos, Márton & Erdos, Gábor & Kis, Tamás, 2009. "Computing lower and upper bounds for a large-scale industrial job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 296-306, August.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:1:p:296-306
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    References listed on IDEAS

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    Cited by:

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    3. Egri, Péter & Váncza, József, 2013. "A distributed coordination mechanism for supply networks with asymmetric information," European Journal of Operational Research, Elsevier, vol. 226(3), pages 452-460.
    4. Bürgy, Reinhard & Bülbül, Kerem, 2018. "The job shop scheduling problem with convex costs," European Journal of Operational Research, Elsevier, vol. 268(1), pages 82-100.

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