A two-level based genetic algorithm for solving the soft-clustered vehicle routing problem

Abstract

The soft-clustered vehicle routing problem (Soft-CluVRP) is a relaxation of the clustered vehicle routing problem (CluVRP), which in turn is a variant of the generalized vehicle routing problem (GVRP). The aim of the Soft-CluVRP is to look for a minimum cost group of routes starting and ending at a given depot to a set of customers partitioned into a priori defined, mutually exclusive and exhaustive clusters, satisfying the capacity constraints of the vehicles and with the supplementary property that all the customers from the same cluster have to be supplied by the same vehicle. The considered optimization problem is NP-hard, that is why we proposed a two-level based genetic algorithm in order to solve it. The computational results reported on a set of existing benchmark instances from the literature, prove that our novel solution approach provides high-quality solutions within acceptable running times.