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Combining statistical learning with metaheuristics for the multi-depot vehicle routing problem with market segmentation

Autor
Ferrer, A.; Calvet , L.; Juan, A.; Masip, D.; Gomes , M. Isabel
Tipus d'activitat
Article en revista
Revista
Computers and industrial engineering
Data de publicació
2016-02
Volum
April
Pàgina inicial
93
Pàgina final
104
DOI
https://doi.org/10.1016/j.cie.2016.01.016 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0360835216300092 Obrir en finestra nova
Resum
In real-life logistics and distribution activities it is usual to face situations in which the distribution of goods has to be made from multiple warehouses or depots to the nal customers. This problem is known as the Multi-Depot Vehicle Routing Problem (MDVRP), and it typically includes two sequential and correlated stages: (a) the assignment map of customers to depots, and (b) the corresponding design of the distribution routes. Most of the existing work in the literature has focused on minimi...
Paraules clau
Multi-Depot Vehicle Routing Problem, hybrid algorithms, market segmentation applications, statistical learning
Grup de recerca
GNOM - Grup d'Optimització Numèrica i Modelització

Participants

  • Ferrer Biosca, Alberto  (autor)
  • Calvet Liñán, Laura  (autor)
  • Juan, Angel A.  (autor)
  • Masip Rodó, David  (autor)
  • Gomes, M. Isabel  (autor)