Multi-objective Evolutionary Approach for Optimizing a Demand Responsive Transport

In this paper, we address the Demand Responsive Transport (DRT) services. A DRT is a flexible transportation service that provides transport on demand, being especially useful in sparsely inhabited areas, which deal with a lack of transportation service. Users formulate requests specifying desired locations and times of pickup and delivery. The vehicle routes are planned and scheduled based on these requests minimizing a set of objectives, like costs and user inconvenience, while respecting a set of constraints imposed by the passengers and vehicles, as time windows and capacity. We adapt a formulation and propose a multi-objective evolutionary algorithm (MOEA) with feasibility-preserving operators. To compare and validate our approach, a MOEA proposed in the literature was reimplemented. Computational experiments were performed on benchmark instances and the results were analyzed by quality indicators widely used for multi-objective algorithms comparison. The proposed algorithm proved to be better in all indicators for all instances.