Optimizing fuel consumption on inland waterway networks: Local search heuristic for lock scheduling. (June 2022)

• Record Type: Journal Article
• Authors: Golak, Julian Arthur Pawel; Defryn, Christof; Grigoriev, Alexander
• Is Part Of: Omega. Volume 109(2022)
• Publication Date: 2022-06
• Subjects: AIS Data -- Inland waterway operations -- Local search heuristic -- Mixed-Integer programming; 00-01 -- 99-00; Management -- Periodicals; 658.4005
• DOI: 10.1016/j.omega.2021.102580
• Languages: English
• ISSNs: 0305-0483

Abstract

Highlights: Minimizing the aggregated fuel consumption on an inland waterway network. Mathematical programming formulation of the speed optimization problem. Local search-based heuristic that allows scalability towards realistic input instances. Computational experiments conducted using real AIS data. Abstract: Fuel consumption and CO 2 emission are among the main criteria to assess the environmental and economical impact of vessels on inland waterways. Both criteria, however, are directly affected by the vessels' sailing speed. In this paper, we present a mathematical programming formulation of the speed optimization problem, which aims at minimizing the aggregated fuel consumption on an inland waterway network. The network can consist of multiple river segments, connected by a set of locks, without restrictions on the configuration. To allow scalability towards realistic waterway networks, we also propose a local-search based heuristic to optimize the speed for individual vessels. We evaluate the effectiveness of the heuristic by comparing it to solving the exact mathematical programming formulation. For all computational experiments, we make use of real AIS data from a section of the Dutch river network. We observe that the heuristic is able to construct a high quality solution in realistic problem settings within reasonable amount of computation time.