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Metaheuristic Approaches for the Fleet Size and Mix Vehicle Routing Problem with Time Windows and Step Cost Functions

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Computational Logistics (ICCL 2020)

Abstract

The vehicle routing problem is a traditional combinatorial problem with practical relevance for a wide range of industries. In the literature, several attributes have been tackled by dedicated methods in order to better reflect real-life situations. This article addresses the fleet size and mix vehicle routing problem with time windows in which companies hire a third-party logistics company. The shipping charges considered in this work are calculated using step cost functions, in which values are determined according to the type of vehicle and the total distance traveled, with fixed values for predefined distance ranges. The problem is solved with three different metaheuristic methods: Variable Neighborhood Search (VNS), Greed Randomized Adaptive Search Procedure (GRASP) and a hybrid proposition that combines both. The methods are examined through a computational comparative analysis in 168 benchmark instances from the literature, small-sized instances with known optimal solution, and 3 instances based on a real problem from the civil construction industry. The numerical experiments show that the proposed methods are efficient and show strong performance in different scenarios.

Supported by FAPESP (grants 2016/01860-1 and 2013/07375-0) and CNPq (grant 306083/2016-7).

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Correspondence to João L. V. Manguino .

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Manguino, J.L.V., Ronconi, D.P. (2020). Metaheuristic Approaches for the Fleet Size and Mix Vehicle Routing Problem with Time Windows and Step Cost Functions. In: Lalla-Ruiz, E., Mes, M., Voß, S. (eds) Computational Logistics. ICCL 2020. Lecture Notes in Computer Science(), vol 12433. Springer, Cham. https://doi.org/10.1007/978-3-030-59747-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-59747-4_15

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