An adaptive large neighborhood search heuristic for the multi-port continuous berth allocation problem

Bernardo Martin-Iradi*, Dario Pacino, Stefan Ropke

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

In this paper, we study a problem that integrates the vessel scheduling problem with the berth allocation into a collaborative problem denoted as the multi-port continuous berth allocation problem (MCBAP). This problem optimizes the berth allocation of a set of ships simultaneously in multiple ports while also considering the sailing speed of ships between ports. Due to the highly combinatorial character of the problem, exact methods struggle to scale to large-size instances, which points to exploring heuristic methods. We present a mixed-integer problem formulation for the MCBAP and introduce an adaptive large neighborhood search (ALNS) algorithm enhanced with a local search procedure to solve it. The computational results highlight the method's suitability for larger instances by providing high-quality solutions in short computational times. Practical insights indicate that the carriers’ and terminal operators’ operational costs are impacted in different ways by fuel prices, external ships at port, and the modeling of a continuous quay.

Original languageEnglish
JournalEuropean Journal of Operational Research
Volume316
Issue number1
Pages (from-to)152-167
Number of pages16
ISSN0377-2217
DOIs
Publication statusPublished - 2024

Keywords

  • Berth allocation problem
  • Container terminal
  • Heuristics
  • OR in maritime industry
  • Speed optimization

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