A parallel time-dependent multimodal shortest path algorithm based on geographical partitioning

This paper deals with the multi-objective shortest path problem in the context of time-dependent transportation networks. We all know that there is rarely a unique global solution that is efficient when optimizing several objectives simultaneously. But rather, it exists a set of optimums of equivalent solutions known as pareto-optimal front. Thus, the goal of multi-objective strategies is to generate a set of non-dominated solutions as an approximation to this front. In this paper, we focus on the computation of pareto front. We discussed two approaches. The first one is exact Martins´s algorithm while second algorithm is based on NSGA-II. In each case, we present various test instances to prove the performances and the limitations of our two approaches.