SUSTAINABLE INTERMODAL FREIGHT BY ROUTE CHOICE WITH PRACTICALITY CONSTRAINTS

The questions that arise are: how to transport goods to the end customer with fewer impacts on the society and the environment, while ensuring a reasonable travel time and cost in order to satisfy the stakeholders? How to find a trade-off between the economic and ecologic goals? The present contribution aims at finding some answers to these questions by building a decision support system for transportation mode and path choice in an intermodal network. So, the goal of our study is to propose an analytic model for environmental and societal impacts computing within an intermodal transportation system. This model injects the route selection depending on the loading factor, the volume of goods transported, the weight of goods and the distance through a filling penalty. From this model, we built a multiobjective shortest path problem which is going to be solving by a multiobjective ant colony algorithm. We have built an algorithm called MOSPACO (Ant Colony Optimization for Multiobjective Shortest Path) by modifying the traditional ant colony algorithm. In our study we consider the optimization of seven objectives. The overall goal of this algorithm is to build a decision support system for decision makers and policy makers in transport and logistics. This decision support systems offer a set of optimal path with the best compromise environment/economy. The remainder of the paper is organized as follow: the section 2 presents the relevant literature review about supply chain management and sustainable transportation systems, the section 3 is a brief literature review about multiobjective shortest path problem, the mathematical model is presented in section 4, the section 5 presents the ant colony algorithm that we build and the section 6 is about the implementation of this algorithm.