An ELS-based approach with dynamic probabilities management in local search for the Dial-A-Ride Problem

This paper addresses the Dial-A-Ride Problem (DARP) which is used to model on-demand transportation services. This kind of transportation is quickly becoming an essential service for modern public mobility or logistics providers. In the DARP, a set of transportation requests has to be handled by a fleet of vehicles. Each request corresponds to a client to be transported from a pickup point to a delivery point. The routing costs have to be minimized, while respecting a set of constraints including time windows on nodes, maximum riding time per client and a maximal total duration of trips.An Evolutionary Local Search (ELS) based approach is proposed to solve this problem. A new greedy randomized heuristic to compute initial solutions is developed. A dynamic probabilities management mechanism is used in the local search to improve the convergence. The method is benchmarked on a classic set of instances from the literature and it is compared against state of the art methods. The numerical results show the effectiveness of this approach.