The Accessibility Vehicle Routing Problem. (20th January 2018)

• Record Type: Journal Article
• Authors: Ibarra-Rojas, O.J.; Hernandez, L.; Ozuna, L.
• Is Part Of: Journal of cleaner production. Volume 172(2018)
• Page Start: 1514
• Page End: 1528
• Publication Date: 2018-01-20
• Subjects: Accessibility -- Vehicle Routing Problem -- Mixed-integer programming -- Iterated local search; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2017.10.249
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: In a distribution process where the demand relates to essential products or services, is important to consider the access for people to fulfill their needs. In particular, for land use and urban transportation planning, accessibility relates to appropriately allocating opportunities to satisfy a demand or provide a service considering the cost of mobility. Measuring accessibility is a challenging task, indeed, it depends on the context of the study and has not been properly considered in the definition of vehicle routing problems, which are commonly used to represent distribution processes. In the study reported here, we addressed a vehicle routing problem to optimize accessibility based on six indicators: the number of zones with access to opportunities with delimited mobility, the number of zones covered by the route, the cost of travel, the distance to the nearest opportunity, the number of opportunities, and geographical disaggregation. We defined a mixed-integer linear formulation for the proposed problem that we used to show the potential benefits of our approach compared with a maximum coverage vehicle routing problem for small instances. In turn, we designed an iterated local search algorithm and analyzed its efficiency according to a benchmark of randomly generated instances. Numerical results show that we obtain high-quality solutions for acceptable computational times.