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A Permutation-Based Neighborhood for the Blocking Job-Shop Problem with Total Tardiness Minimization

In: Operations Research Proceedings 2017

Author

Listed:
  • Julia Lange

    (Otto-von-Guericke-Universität Magdeburg)

  • Frank Werner

    (Otto-von-Guericke-Universität Magdeburg)

Abstract

The consideration of blocking constraints refers to the absence of buffers in a production system. A job-shop scheduling problem with a total tardiness objective is NP-hard even without blocking constraints and mathematical programming results indicate the necessity of heuristics. The neighborhood is one of its main components. In contrast to classical job-shop scheduling, a permutation of operations does not necessarily define a feasible schedule. A neighbor is determined by an adjacent pairwise interchange (API) of two operations on a machine and the resulting permutation of operations is modified to regain feasibility while maintaining the given API. The neighborhood is implemented in a simulated annealing and tested on train-scheduling-inspired problems as well as benchmark instances. The heuristic method obtains optimal and near-optimal solutions for small instances and outperforms a given MIP formulation for some of the larger ones.

Suggested Citation

  • Julia Lange & Frank Werner, 2018. "A Permutation-Based Neighborhood for the Blocking Job-Shop Problem with Total Tardiness Minimization," Operations Research Proceedings, in: Natalia Kliewer & Jan Fabian Ehmke & Ralf Borndörfer (ed.), Operations Research Proceedings 2017, pages 581-586, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-89920-6_77
    DOI: 10.1007/978-3-319-89920-6_77
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    Cited by:

    1. Evgeny Gafarov & Frank Werner, 2019. "Two-Machine Job-Shop Scheduling with Equal Processing Times on Each Machine," Mathematics, MDPI, vol. 7(3), pages 1-11, March.

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