A Decision Model Based on a GRASP Genetic Algorithm for Solving the Vehicle Routing Problem

Hiba Yahyaoui, Saoussen Krichen and Abdelkader Dekdouk
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Hiba Yahyaoui: ISG, Tunis, Tunisia
Saoussen Krichen: ISG, Tunis, Tunisia
Abdelkader Dekdouk: Dhofar University, Salalah, Oman

International Journal of Applied Metaheuristic Computing (IJAMC), 2018, vol. 9, issue 2, 72-90

Abstract: In this paper, the authors address a delivery process with time requirements in the supply chain, stated as follows: orders launched from customers are centralized and assigned to firms' depots for the delivery process. The consideration of a depot and a set of customers belonging to different firms, is seen as a VRPTW that serves n customers using a subset of vehicles. Implemented in this article is a DSS that handles the delivering activity in the supply chain. The DSS embeds a Greedy Randomized Adaptive Search Procedure (GRASP) and Genetic components for generating promising solutions in a concurrently run time. Simulation results are conducted on Solomon's benchmarks. The DSS records very competitive results regarding state-of-the-art approaches.

Date: 2018
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