An agile and reactive biased-randomized heuristic for an agri-food rich vehicle routing problem
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Rafael D. Tordecilla [1] [2] ; Pedro J. Copado Méndez [1] ; Javier Panadero [1] ; Leandro do C. Martins [1] ; Ángel A. Juan [1]
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[1] Universitat Oberta de Catalunya
Universitat Oberta de Catalunya
Barcelona, España
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[2] Universidad de La Sabana
Universidad de La Sabana
Colombia
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- Localización: R-evolucionando el transporte [Recurso electrónico]: XIV Congreso de Ingeniería del Transporte. Universidad de Burgos 6, 7 y 8 de julio 2021 / Hernán Gonzalo Orden (ed. lit.)
, Marta Rojo Arce (ed. lit.), 2021, ISBN 978-84-18465-12-3, págs. 1085-1096 - Idioma: inglés
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Resumen
Operational problems in agri-food supply chains usually show characteristics that are scarcely addressed by traditional academic approaches. These characteristics make an already NP-hard problem even more challenging; hence, this problem requires the use of tailor-made algorithms in order to solve it efficiently. This work addresses a rich vehicle routing problem in a real-world agri-food supply chain. Different types of animal food products are distributed to raising-pig farms. These products are incompatible, i.e., multi-compartment heterogeneous vehicles must be employed to perform the distribution activities. The problem considers constraints regarding visit priorities among farms, and not-allowed access of large vehicles to a subset of farms. Finally, a set of flat tariffs are employed to formulate the cost function. This problem is solved employing a reactive savings-based biased-randomized heuristic, which does not require any time-costly parameter fine-tuning process. Our results show savings in both cost and traveled distance when compared with the real supply chain performance.
