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A column generation based heuristic for the generalized vehicle routing problem with time windows

Yuan Yuan, Diego Cattaruzza, Maxime Ogier, Frédéric Semet and Daniele Vigo

Transportation Research Part E: Logistics and Transportation Review, 2021, vol. 152, issue C

Abstract: The generalized vehicle routing problem with time windows (GVRPTW) is defined on a directed graph G=(V,A) where the vertex set V is partitioned into clusters. One cluster contains only the depot, where is located a homogeneous fleet of vehicles, each with a limited capacity. The other clusters represent customers. A demand is associated with each cluster. Inside a cluster, the vertices represent the possible locations of the customer. A time window is associated with each vertex, during which the visit must take place if the vertex is visited. The objective is to find a set of routes such that the total traveling cost is minimized, exactly one vertex per cluster is visited, and all the capacity and time constraints are respected. This paper presents a set covering formulation for the GVRPTW which is used to provide a column generation based heuristic to solve it. The proposed solving method combines several components including a construction heuristic, a route optimization procedure, local search operators and the generation of negative reduced cost routes. Experimental results on benchmark instances show that the proposed algorithm is efficient and high-quality solutions for instances with up to 120 clusters are obtained within short computation times.

Keywords: Generalized vehicle routing problem; Time windows; Last mile delivery; Delivery options; Trunk/in-car delivery (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tre.2021.102391

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Transportation Research Part E: Logistics and Transportation Review is currently edited by W. Talley

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