A fuzzy TOPSIS approach for finding shortest path in multimodal transportation networks

Abstract

The paper must have abstract. In this paper, we present a fuzzy shortest path algorithm in Multimodal Transportation Networks (MTN). To extend the classical problem of shortest path, an innovative framework is presented, which integrates Fuzzy Logic and Multi Criteria Decision Making (MCDM) techniques. The aim is to deal with an efficient design for the multimodal shortest path computation taking into accounts not only the expected travel time, but also additional constraints such as: delays at mode and arc switching points, costs, viability of the sequence of the used modes and the number of modal transfers. To this scope, all previously mentioned constraints are evaluated following a new approach based on Fuzzy Logic and aggregated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to find the shortest path in MTN. A numerical example is also presented to demonstrate the computational process of the proposed approach.

A bi-objective model for uncertain multi-modal shortest path problems

“…Galvez-Fernandez et al [26] introduced a transfer graph approach, which was believed to better abstract the distributed nature of real transport information sources, to calculate the best paths in multi-modal networks. Yamani et al [27] presented a fuzzy shortest path algorithm in multi-modal transportation networks, which concerned about not only the path cost but also the path time which consisted of travel time and delays.…”

“…Thus, investigating the multi-modal shortest path problem in the indeterministic environment becomes a significant and challenging issue for the practical applications. We here note that finding the shortest path in a multi-modal network has been studied in various forms such as static [22], dynamic [26,28], stochastic [29,30], fuzzy [27], constrained [23], and multi-criteria [24,25,31,32]. However, to the best of our knowledge, few studies have been considered in the uncertain environment within the framework of uncertain programming.…”