A matheuristic for a multimodal long haul routing problem

• Published in: EURO Journal on Transportation and Logistics Vol. 8; no. 4; pp. 397 - 433
• Main Authors: Wolfinger, David, Tricoire, Fabien, Doerner, Karl F.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Elsevier B.V 01.12.2019; Springer Berlin Heidelberg; Elsevier Limited
• Subjects: 90B06; 90C11; Alliances; Business and Management; Column generation; Cost control; Freight forwarding; Intermodal transportation; Iterated local search; Logistics; Management Science; Mathematics Subject Classification; Minimum cost; Multimodal transportation; Multimodal transportation systems; Operations Research; Operations Research/Decision Theory; Optimization; Research Paper; Road transportation; Column generation; Multimodal transportation; Mathematics Subject Classification; 90B06; 90C11; Iterated local search
• ISSN: 2192-4376; 2192-4384
• DOI: 10.1007/s13676-018-0131-1

We address a planning problem faced by logistics service providers who transport freight over long distances. Given a set of transportation requests, where the origin and the destination of each request are located far apart from each other, a logistics service provider must find feasible vehicle routes to fulfil those requests at minimum cost. When transporting freight over long distances, multimodal transportation provides a viable alternative to traditional unimodal road transportation. We introduce this new problem, which we call the multimodal long haul routing problem (MMLHRP), and present a mathematical formulation for it. Furthermore, we propose a matheuristic, using iterated local search within a column generation framework, for solving the MMLHRP. Results show that large cost savings can be achieved through multimodal transportation compared to unimodal road transportation.