Solving the Feeder Vehicle Routing Problem using ant colony optimization

Ying Hua Huang, Carola A. Blazquez, Shan Huen Huang, Germán Paredes-Belmar, Guillermo Latorre-Nuñez

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

32 Citas (Scopus)


This paper studies the Feeder Vehicle Routing Problem (FVRP), a new variant of the vehicle routing problem (VRP), in which each customer is served by either a large (truck) or a small vehicle (motorcycle). In this particular type of delivery, the trucks and the motorcycles must depart from the depot, visit the customers, and eventually return to the depot. During the delivery process, the motorcycles travel to the truck locations for reloading. The ant colony optimization (ACO) algorithm is employed for solving the problem with the objective of determining the number of dispatching sub-fleets and optimal routes to minimize the total cost (fixed route and travel costs). Three benchmark datasets are generated to examine the performance of the FVPR. For comparison purposes, all instances are executed by dispatching only trucks as in the traditional VRP and a four-stage hierarchical heuristic. Additionally, ACO is compared to optimal solutions for small instances. The results indicate that the proposed ACO algorithm yields promising solutions particularly for large instances within a reasonable time frame in an efficient manner.

Idioma originalInglés
Páginas (desde-hasta)520-535
Número de páginas16
PublicaciónComputers and Industrial Engineering
EstadoEn prensa - 1 ene. 2018

Áreas temáticas de ASJC Scopus

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  • Ingeniería (todo)


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