On solving the 2L-CVRP using an adaptive chemical reaction algorithm: postal transportation real-case

Abstract

The postal sector plays a crucial role in enhancing and advancing services for businesses and citizens through its diverse services. Hence, optimizing the routing system collecting and transporting letters and parcels is a vital element within a well-rounded delivery management system. We model the problem as a Capacitated vehicle routing problem (CVRP) with two-dimensional loading constraints (2L-CVRP). This involves designing a set of routes that start and end at a central depot. Moreover, items in each vehicle trip must satisfy the two-dimensional orthogonal packing constraints. The main objective is to optimize the total transportation costs using a homogeneous vehicle fleet. Due to the NP-hardness of the 2L-CVRP, we proposed an adaptive chemical reaction optimization (ACRO) metaheuristic to generate potential solutions. The algorithm adjusts its parameters and is intelligent search strategies during the optimization process based on the characteristics of the problem. Consequently, the algorithm can exploit and explore new regions of the search space. We compared our results with state-of-the-art meta-heuristics using 2L-CVRP benchmark instances from the literature. The results showed competitive solutions regarding the optimal ones. The empirical results, derived from benchmark datasets comprising a total of 180 instancesrove the high competitiveness of the proposed ACRO. It achieves a 67% success rate out of 36 instances for class 1 and a 59% success rate out of 144 instances for class 2–5 in terms of obtained solutions. In addition to benchmarking, we considered a real-world case study from the Tunisian Post Office. The ACRO results outperform the scenario adopted by the post office.