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A fast and effective MIP-based heuristic for a selective and periodic inventory routing problem in reverse logistics

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  • Cárdenas-Barrón, Leopoldo E.
  • Melo, Rafael A.

Abstract

We consider an NP-hard selective and periodic inventory routing problem (SPIRP) in a waste vegetable oil collection environment. This SPIRP arises in the context of reverse logistics where a biodiesel company has daily requirements of oil to be used as raw material in its production process. These requirements can be fulfilled by using the available inventory, collecting waste vegetable oil or purchasing virgin oil. The problem consists in determining a period (cyclic) planning for the collection and purchasing of oil such that the total collection, inventory and purchasing costs are minimized, while meeting the company’s oil requirements and all the operational constraints. We propose a MIP-based heuristic which solves a relaxed model without routing, constructs routes taking into account the relaxation’s solution and then improves these routes by solving the capacitated vehicle routing problem associated to each period. Following this approach, an a posteriori performance guarantee is ensured, as the approach provides both a lower bound and a feasible solution. The performed computational experiments show that the MIP-based heuristic is very fast and effective as it is able to encounter near optimal solutions with low gaps within seconds, improving several of the best known results using just a fraction of the time spent by a state-of-the-art heuristic. A remarkable fact is that the proposed MIP-based heuristic improves over the best known results for all the large instances available in the literature.

Suggested Citation

  • Cárdenas-Barrón, Leopoldo E. & Melo, Rafael A., 2021. "A fast and effective MIP-based heuristic for a selective and periodic inventory routing problem in reverse logistics," Omega, Elsevier, vol. 103(C).
  • Handle: RePEc:eee:jomega:v:103:y:2021:i:c:s0305048321000037
    DOI: 10.1016/j.omega.2021.102394
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    References listed on IDEAS

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    1. Fokkema, Jan Eise & Land, Martin J. & Coelho, Leandro C. & Wortmann, Hans & Huitema, George B., 2020. "A continuous-time supply-driven inventory-constrained routing problem," Omega, Elsevier, vol. 92(C).
    2. Qiu, Yuzhuo & Qiao, Jun & Pardalos, Panos M., 2019. "Optimal production, replenishment, delivery, routing and inventory management policies for products with perishable inventory," Omega, Elsevier, vol. 82(C), pages 193-204.
    3. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    4. Coelho, Leandro C. & Laporte, Gilbert, 2014. "Improved solutions for inventory-routing problems through valid inequalities and input ordering," International Journal of Production Economics, Elsevier, vol. 155(C), pages 391-397.
    5. Soysal, Mehmet & Bloemhof-Ruwaard, Jacqueline M. & Haijema, Rene & van der Vorst, Jack G.A.J., 2015. "Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty," International Journal of Production Economics, Elsevier, vol. 164(C), pages 118-133.
    6. Neves-Moreira, Fábio & Almada-Lobo, Bernardo & Cordeau, Jean-François & Guimarães, Luís & Jans, Raf, 2019. "Solving a large multi-product production-routing problem with delivery time windows," Omega, Elsevier, vol. 86(C), pages 154-172.
    7. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    8. Aksen, Deniz & Kaya, Onur & Sibel Salman, F. & Tüncel, Özge, 2014. "An adaptive large neighborhood search algorithm for a selective and periodic inventory routing problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 413-426.
    9. Raa, Birger, 2015. "Fleet optimization for cyclic inventory routing problems," International Journal of Production Economics, Elsevier, vol. 160(C), pages 172-181.
    10. Leandro C. Coelho & Jean-François Cordeau & Gilbert Laporte, 2014. "Thirty Years of Inventory Routing," Transportation Science, INFORMS, vol. 48(1), pages 1-19, February.
    11. Romain Montagné & Michel Gamache & Michel Gendreau, 2019. "A shortest path-based algorithm for the inventory routing problem of waste vegetable oil collection," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(6), pages 986-997, June.
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    2. Mahmutoğulları, Özlem & Yaman, Hande, 2023. "A Branch-and-Cut Algorithm for the Inventory Routing Problem with Product Substitution," Omega, Elsevier, vol. 115(C).

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