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Sequential and parallel large neighborhood search algorithms for the periodic location routing problem

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  • Hemmelmayr, Vera C.

Abstract

We propose a large neighborhood search (LNS) algorithm to solve the periodic location routing problem (PLRP). The PLRP combines location and routing decisions over a planning horizon in which customers require visits according to a given frequency and the specific visit days can be chosen. We use parallelization strategies that can exploit the availability of multiple processors. The computational results show that the algorithms obtain better results than previous solution methods on a set of standard benchmark instances from the literature.

Suggested Citation

  • Hemmelmayr, Vera C., 2015. "Sequential and parallel large neighborhood search algorithms for the periodic location routing problem," European Journal of Operational Research, Elsevier, vol. 243(1), pages 52-60.
    • Handle: RePEc:eee:ejores:v:243:y:2015:i:1:p:52-60
    DOI: 10.1016/j.ejor.2014.11.024
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    3. Ling Liu & Sen Liu, 2020. "Integrated Production and Distribution Problem of Perishable Products with a Minimum Total Order Weighted Delivery Time," Mathematics, MDPI, vol. 8(2), pages 1-18, January.
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    5. Olmez, Omer Berk & Gultekin, Ceren & Balcik, Burcu & Ekici, Ali & Özener, Okan Örsan, 2022. "A variable neighborhood search based matheuristic for a waste cooking oil collection network design problem," European Journal of Operational Research, Elsevier, vol. 302(1), pages 187-202.
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    7. Schryen, Guido, 2020. "Parallel computational optimization in operations research: A new integrative framework, literature review and research directions," European Journal of Operational Research, Elsevier, vol. 287(1), pages 1-18.

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