A Novel Adaptive Genetic Algorithm for Dynamic Vehicle Routing Problem With Backhaul and Two-Dimensional Loading Constraints: A Case in Tunisian Posta

Ines Sbai and Saoussen Krichen
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Ines Sbai: Institut Supérieur de Gestion de Tunis, LARODEC Laboratory, Université de Tunis, Tunis, Tunisia
Saoussen Krichen: Institut Supérieur de Gestion de Tunis, LARODEC Laboratory, Université de Tunis, Tunis, Tunisia

International Journal of Applied Metaheuristic Computing (IJAMC), 2022, vol. 13, issue 1, 1-34

Abstract: In this paper, we consider an extension of the Dynamic Vehicle Routing Problem with Backhauls integrated with two-dimensional loading problem called DVRPB with 2D loading constraints (2L-DVRPB). In the VRPB, a vehicle can deliver (Linehaul) then collect goods from customers (backhaul) and bring back to the depot. Once customer demand is formed by a set of two-dimensional items the problem will be treat as a 2L-VRPB. The 2L-VRPB has been studied on the static case. However, in most real-life application, new customer requests can be happen over time of backhaul and thus perturb the optimal routing schedule that was originally invented. This problem has not been analysed sofar in the literature. The 2L-DVRPB is an NP-Hard problem, so, we propose to use a Genetic algorithm for routing and a packing problems. We applied our approach in a real case study of the Regional Post Office of the city of Jendouba in the North of Tunisia. Results indicate that the AGA approach is considered as the best approach in terms of solutions quality for a real world routing system.

Date: 2022
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