2024-03-29T11:15:10Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/69112022-10-17T09:30:49Zcom_10259.4_104com_10259_2604col_10259_6848
An agile and reactive biased-randomized heuristic for an agri-food rich vehicle routing problem
Tordecilla, Rafael D.
Copado-Méndez, Pedro J.
Panadero, Javier
Martins, Leandro do C.
Juan, Angel A.
Logística
Operaciones
Logistics
Operations
Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos
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., multicompartment
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.
2022-09-19T09:42:56Z
2022-09-19T09:42:56Z
2021-07
info:eu-repo/semantics/conferenceObject
978-84-18465-12-3
http://hdl.handle.net/10259/6911
10.36443/10259/6911
eng
R-Evolucionando el transporte
http://hdl.handle.net/10259/6490
https://doi.org/10.36443/9788418465123
info:eu-repo/grantAgreement/EC/H2020/282300206-UC005/EU/Internet of Food and Farm 2020
info:eu-repo/grantAgreement/UdLS//INGPhD-12-2020
info:eu-repo/semantics/openAccess
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