An adaptive large neighbourhood search heuristic for routing and scheduling feeder vessels in multi-terminal ports

Erik Orm Hellsten, David Sacramento and David Pisinger

European Journal of Operational Research, 2020, vol. 287, issue 2, 682-698

Abstract: This paper proposes an Adaptive Large Neighbourhood Search heuristic for solving the Port Scheduling Problem, the problem of scheduling feeder vessels’ operations in multi-terminal ports. Each vessel has a number of operations to perform at different terminals within the port, and each terminal can only serve a single vessel at a time. The resulting problem is a general shop-like problem, with a variety of additional operational constraints. The objective is to let the vessels depart from the port as early as possible, as this allows them to sail at reduced speed to the next port, saving large amounts of fuel; as well as scheduling operations early, which leaves more slack for later and hence makes the system more robust. The developed Adaptive Large Neighbourhood Search heuristic works with the order of operations, and assigns the start times of the operations first as part of the solution evaluation. To conduct the computational experiments, a large set of benchmark test instances, denoted PortLib, was developed, and the performance of the heuristic was compared to that of a commercial solver. The results show that the heuristic in general finds better solutions, even with significantly shorter run times.

Keywords: OR in maritime industry; Port operations; General shop scheduling; ALNS (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:287:y:2020:i:2:p:682-698

DOI: 10.1016/j.ejor.2020.04.050

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