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Project scheduling with inventory constraints

Author

Listed:
  • Klaus Neumann
  • Christoph Schwindt

Abstract

Inventory constraints refer to so-called cumulative resources, which can store a single or several different products and have a prescribed minimum and maximum inventory, where the inventory is depleted and replenished over time. Some additional applications of cumulative resources, e.g. to investment projects, are also discussed in this paper. We study some properties of the feasible region of the project scheduling problem with inventory constraints and general temporal constraints and especially show how to resolve so-called resource conflicts. The feasible region represents the intersection of a union of polyhedral cones with the polyhedron of time-feasible solutions. These results can be exploited for constructing an efficient branch-and-bound algorithm which enumerates alternatives to avoid stock shortage and surplus by introducing precedence constraints between disjoint sets of events. Finally, we sketch how the procedure can be truncated to a filtered beam search heuristic. An experimental performance analysis shows that problem instances with 100 events and five cumulative resources can be solved in less than one minute. Copyright Springer-Verlag Berlin Heidelberg 2003

Suggested Citation

  • Klaus Neumann & Christoph Schwindt, 2003. "Project scheduling with inventory constraints," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 56(3), pages 513-533, January.
    • Handle: RePEc:spr:mathme:v:56:y:2003:i:3:p:513-533
    DOI: 10.1007/s001860200251
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    Citations

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    Cited by:

    1. van der Beek, T. & Souravlias, D. & van Essen, J.T. & Pruyn, J. & Aardal, K., 2024. "Hybrid differential evolution algorithm for the resource constrained project scheduling problem with a flexible project structure and consumption and production of resources," European Journal of Operational Research, Elsevier, vol. 313(1), pages 92-111.
    2. Sandra Ulrich Ngueveu & Christian Artigues & Nabil Absi & Safia Kedad-Sidhoum, 2022. "Lower and upper bounds for scheduling energy-consuming tasks with storage resources and piecewise linear costs," Journal of Heuristics, Springer, vol. 28(1), pages 93-120, February.
    3. Györgyi, Péter & Kis, Tamás, 2017. "Approximation schemes for parallel machine scheduling with non-renewable resources," European Journal of Operational Research, Elsevier, vol. 258(1), pages 113-123.
    4. Sciau, Jean-Baptiste & Goyon, Agathe & Sarazin, Alexandre & Bascans, Jérémy & Prud’homme, Charles & Lorca, Xavier, 2024. "Using constraint programming to address the operational aircraft line maintenance scheduling problem," Journal of Air Transport Management, Elsevier, vol. 115(C).
    5. Davari, Morteza & Ranjbar, Mohammad & De Causmaecker, Patrick & Leus, Roel, 2020. "Minimizing makespan on a single machine with release dates and inventory constraints," European Journal of Operational Research, Elsevier, vol. 286(1), pages 115-128.

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