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Planning of multi-product pipelines by economic lot scheduling models

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  • Kirschstein, Thomas

Abstract

In chemical and petroleum industry pipelines are one of the most important means of transportation. However, flexibility of pipeline transport systems is limited by many restrictions. Therefore, the planning of pipeline operations is a crucial part of logistics management in these industries. A particularly challenging problem is the pipeline scheduling which is concerned with finding the sequences, times, and sizes of batch injections in pipeline systems. This paper specifically studies the underlying core scheduling problem by assuming a simple multi-product pipeline system. It is shown that finding a sequence of batches which minimizes stock holding and setup costs in the long run is an NP-hard scheduling problem, namely a variant of the economic lot scheduling problem (ELSP) with additional constraints. Therefore, a powerful heuristic for the sequence-dependent ELSP is adapted and extended to meet the requirements of the outlined pipeline scheduling problem. The application of the heuristic is illustrated by case studies from chemical and petroleum industry.

Suggested Citation

  • Kirschstein, Thomas, 2018. "Planning of multi-product pipelines by economic lot scheduling models," European Journal of Operational Research, Elsevier, vol. 264(1), pages 327-339.
    • Handle: RePEc:eee:ejores:v:264:y:2018:i:1:p:327-339
    DOI: 10.1016/j.ejor.2017.06.014
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    Cited by:

    1. Meira, William Hitoshi Tsunoda & Magatão, Leandro & Relvas, Susana & Barbosa-Póvoa, Ana Paula & Neves, Flávio & Arruda, Lúcia V.R., 2018. "A matheuristic decomposition approach for the scheduling of a single-source and multiple destinations pipeline system," European Journal of Operational Research, Elsevier, vol. 268(2), pages 665-687.
    2. Mostafaei, Hossein & Castro, Pedro M. & Oliveira, Fabricio & Harjunkoski, Iiro, 2021. "Efficient formulation for transportation scheduling of single refinery multiproduct pipelines," European Journal of Operational Research, Elsevier, vol. 293(2), pages 731-747.
    3. Neda Beheshti Asl & S. A. MirHassani & S. Relvas & F. Hooshmand, 2022. "A novel two-phase decomposition-based algorithm to solve MINLP pipeline scheduling problem," Operational Research, Springer, vol. 22(5), pages 4829-4863, November.
    4. Mostafaei, Hossein & Castro, Pedro M. & Relvas, Susana & Harjunkoski, Iiro, 2021. "A holistic MILP model for scheduling and inventory management of a multiproduct oil distribution system," Omega, Elsevier, vol. 98(C).

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