A hybrid approach to the problem of journey planning with the use of mathematical programming and modern techniques

In the last decades, products and services concerning the transportation of individuals have made the world more interconnected than ever before. Although this fact has enabled people to perform travel-related activities more effectively, neglecting the ecological footprint of those transports has created environmental problems, and as a consequence, for our societies. This study introduces a novel approach for the multi-modal journey planning problem (MMJP) and specifically proposes a hybrid solution algorithm that solves the problem of Environmental MMJP, based both on heuristic and exact algorithms. The algorithm delivers as solutions multi-modal paths that a person can follow and produce the minimum Greenhouse Gas Emissions (GHG) from the different modes of transport that he or she will use while travelling. Given a set of public transport operation schedules, emission calculation models and public network data, a mixed-integer linear programming (MILP) model was developed for the problem, which is solved in combination with the Dijkstra's algorithm in order to deliver the optimal journey. The research is still ongoing for the improvement of the algorithm and the goal is to integrate it in an online platform.