An Efficient Metaheuristic Algorithm for Solving Soft-clustered Vehicle Routing Problems

Abstract

A soft-clustered vehicle routing problem (SoftClu-VRP) is an important variant of the well-known capacitated vehicle routing problem, where customers are partitioned into clusters and all customers of the same cluster must be served by the same vehicle. As a highly useful model for parcel delivery in courier companies, SoftCluVRP is NP-hard. In this work, we propose an efficient metaheuristic algorithm for solving it. Starting from an initial population, it iterates by using a solution recombination operator (to generate a promising offspring solution), a hybrid neighborhood search (to find a high-quality local optimum), and a population updating strategy (to manage a healthy population). Experiments on two groups of 378 widely-used benchmark instances show that it achieves highly competitive performance compared to state-of-the-art algorithms. In particular, our algorithm finds the best upper bounds on 320 instances.