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Resource loading with time windows

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  • Talla Nobibon, Fabrice
  • Leus, Roel
  • Nip, Kameng
  • Wang, Zhenbo

Abstract

Resource loading appears in many variants in tactical (mid-term) capacity planning in multi-project environments. It develops a rough sketch of the resource usage and timing of the work packages of a portfolio of orders. The orders need to be executed within a time horizon organized into periods, each of which has a known number of workers available. Each order has a time window during which it must be executed, as well as an upper and lower bound on the number of workers that can work on this order in a period. The duration of the order is not fixed beforehand, but depends on the number of workers (intensity) with which it is executed. In this article we define three fundamental variants of resource loading and study six special cases that are common to the three variants. We present algorithms for those cases that can be solved either in polynomial time or in pseudo-polynomial time. The remaining cases are proven to be np-complete in the strong sense, and we discuss the existence of approximation algorithms for some of these cases. Finally, we comment on the validity of our results when orders must be executed without preemption. Although inspired by a number of practical applications, this work focuses on the properties of the underlying generic combinatorial problems. Our findings contribute to a better understanding of these problems and may also serve as a reference work for authors looking to design efficient algorithms for similar problems.

Suggested Citation

  • Talla Nobibon, Fabrice & Leus, Roel & Nip, Kameng & Wang, Zhenbo, 2015. "Resource loading with time windows," European Journal of Operational Research, Elsevier, vol. 244(2), pages 404-416.
  • Handle: RePEc:eee:ejores:v:244:y:2015:i:2:p:404-416
    DOI: 10.1016/j.ejor.2015.01.036
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    References listed on IDEAS

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    Cited by:

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    2. Carvalho, Andréa Nunes & Oliveira, Fabricio & Scavarda, Luiz Felipe, 2015. "Tactical capacity planning in a real-world ETO industry case: An action research," International Journal of Production Economics, Elsevier, vol. 167(C), pages 187-203.
    3. Guopeng Song & Tamás Kis & Roel Leus, 2021. "Polyhedral Results and Branch-and-Cut for the Resource Loading Problem," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 105-119, January.

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