A hybrid algorithm for the multi-depot heterogeneous dial-a-ride problem

Abstract

Vehicle routing problems arise in many practical situations in the context of transportation logistics. Among them, we can highlight the problem of transporting customers from origin to destination locations, which is known as the dial-a-ride problem (DARP). This problem consists of designing least-cost routes to serve pickup-and-delivery requests, while meeting capacity, time window, maximum route duration, and maximum ride time constraints. This work proposes a hybrid algorithm to solve single and multi-depot DARP variants where both the demands and vehicle fleet are heterogeneous. The method combines the iterated local search metaheuristic with an exact procedure based on a set partitioning approach. In addition, several procedures were implemented to speedup the local search phase. Extensive computational experiments were conducted on existing and newly proposed benchmark instances in order to evaluate the impact of the different components of the algorithm, and to compare its performance against the best existing method. The results obtained suggest that the proposed algorithm is capable of producing highly competitive results regarding both solution quality and CPU time, and of improving several best known solutions.