Measuring and evaluating hybrid metaheuristics for solving the multi-compartment vehicle routing problem

In this paper, a Multi-Compartment Vehicle Routing Problem (MCVRP) is discussed. The main objective of this problem is to minimize the total traveled distance while using a minimum number of trucks. Different product types are loaded into a fleet of homogeneous trucks with an identical capacity of compartments. For this problem, we present a mathematical model in which the total customer demands for each product must be fully delivered by a single truck and not exceed the truck capacity of the compartment. Moreover, the distance traveled by each truck is subject to a set of constraints in our case study. According to the computational results, the optimization approach can yield us the optimal solution only in the small size instances. For large problem instances, two algorithms to solve the MCVRP are proposed: a hybrid artificial bee colony algorithm and a hybrid self-adaptive general variable neighborhood algorithm. The proposed algorithms are tested using a real case study. The computational results are also compared to existing approaches for measuring and evaluating the performance of the proposed algorithms. (C) 2019 Elsevier Ltd. All rights reserved.