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<dc:title>An agile and reactive biased-randomized heuristic for an agri-food rich vehicle routing problem</dc:title>
<dc:creator>Tordecilla, Rafael D.</dc:creator>
<dc:creator>Copado-Méndez, Pedro J.</dc:creator>
<dc:creator>Panadero, Javier</dc:creator>
<dc:creator>Martins, Leandro do C.</dc:creator>
<dc:creator>Juan, Angel A.</dc:creator>
<dc:subject>Logística</dc:subject>
<dc:subject>Operaciones</dc:subject>
<dc:subject>Logistics</dc:subject>
<dc:subject>Operations</dc:subject>
<dc:subject>Ingeniería civil</dc:subject>
<dc:subject>Transportes</dc:subject>
<dc:subject>Civil engineering</dc:subject>
<dc:subject>Transportation</dc:subject>
<dc:description>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</dc:description>
<dc:description>Operational problems in agri-food supply chains usually show characteristics that are&#xd;
scarcely addressed by traditional academic approaches. These characteristics make an&#xd;
already NP-hard problem even more challenging; hence, this problem requires the use of&#xd;
tailor-made algorithms in order to solve it efficiently. This work addresses a rich vehicle&#xd;
routing problem in a real-world agri-food supply chain. Different types of animal food&#xd;
products are distributed to raising-pig farms. These products are incompatible, i.e., multicompartment&#xd;
heterogeneous vehicles must be employed to perform the distribution&#xd;
activities. The problem considers constraints regarding visit priorities among farms, and&#xd;
not-allowed access of large vehicles to a subset of farms. Finally, a set of flat tariffs are&#xd;
employed to formulate the cost function. This problem is solved employing a reactive&#xd;
savings-based biased-randomized heuristic, which does not require any time-costly&#xd;
parameter fine-tuning process. Our results show savings in both cost and traveled distance&#xd;
when compared with the real supply chain performance.</dc:description>
<dc:description>This work has been partially supported by the Doctoral School of the Universitat Oberta de Catalunya (Spain), the Universidad de La Sabana (Colombia, Grant INGPhD-12-2020), and the EU-IoF2020 project (282300206-UC005).</dc:description>
<dc:date>2022-09-19T09:42:56Z</dc:date>
<dc:date>2022-09-19T09:42:56Z</dc:date>
<dc:date>2021-07</dc:date>
<dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:identifier>978-84-18465-12-3</dc:identifier>
<dc:identifier>http://hdl.handle.net/10259/6911</dc:identifier>
<dc:identifier>10.36443/10259/6911</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>R-Evolucionando el transporte</dc:relation>
<dc:relation>http://hdl.handle.net/10259/6490</dc:relation>
<dc:relation>https://doi.org/10.36443/9788418465123</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/EC/H2020/282300206-UC005/EU/Internet of Food and Farm 2020</dc:relation>
<dc:relation>info:eu-repo/grantAgreement/UdLS//INGPhD-12-2020</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:format>application/pdf</dc:format>
<dc:publisher>Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional</dc:publisher>
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