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A cost minimization heuristic for the pooling problem

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  • Mohammed Alfaki
  • Dag Haugland

Abstract

Pooling and blending are important operations in petrochemical and agricultural industries with high potential economic value. For instance, transporting the natural gas from the production sources to the exit terminals is a complex process where the end products in the terminals consist of a blend of natural gas from different sources. Constraints of particular importance, are restrictions regarding gas quality at terminals and the actual quality of the gas produced at sources. In many situations, intermediate pooling tanks are necessary, implying that an otherwise linear network flow model is transformed into a strongly NP-hard problem recognized as the pooling problem. In this paper, we propose an algorithm for computing good feasible solutions to the pooling problem. In particular, we give a greedy construction method that in each iteration solves a pooling problem instance with only one terminal. Computational experiments demonstrate the merit of the method, which, in the hardest instances, give considerably better results than commercially available local and global optimizers. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Mohammed Alfaki & Dag Haugland, 2014. "A cost minimization heuristic for the pooling problem," Annals of Operations Research, Springer, vol. 222(1), pages 73-87, November.
  • Handle: RePEc:spr:annopr:v:222:y:2014:i:1:p:73-87:10.1007/s10479-013-1433-1
    DOI: 10.1007/s10479-013-1433-1
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    Cited by:

    1. Natashia Boland & Thomas Kalinowski & Fabian Rigterink, 2016. "New multi-commodity flow formulations for the pooling problem," Journal of Global Optimization, Springer, vol. 66(4), pages 669-710, December.
    2. Ahmadreza Marandi & Joachim Dahl & Etienne Klerk, 2018. "A numerical evaluation of the bounded degree sum-of-squares hierarchy of Lasserre, Toh, and Yang on the pooling problem," Annals of Operations Research, Springer, vol. 265(1), pages 67-92, June.
    3. Santanu S. Dey & Akshay Gupte, 2015. "Analysis of MILP Techniques for the Pooling Problem," Operations Research, INFORMS, vol. 63(2), pages 412-427, April.

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