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Wang, R, Nguyen, TT, Li, C, Jenkinson, I, Yang, Z and Kavakeb, S (2018) Optimising discrete dynamic berth allocations in seaports using a Levy Flight based meta-heuristic. Swarm and Evolutionary Computation, 44. pp. 1003-1017. ISSN 2210-6502
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Abstract
Seaports play a vital role in our everyday life: they handle 90% of our world trade goods. Improving seaports' efficiency means improving the efficiency of sending and receiving our goods. In seaports, one of the most important and most expensive operations is how to allocate vessels to berths. In this paper, we solve this problem by proposing a new meta-heuristic, which combines the nature-inspired Levy Flight random walk with local search, while taking into account tidal windows. With our algorithm, we meet the following goals: (i) to minimise the cost of all vessels while staying in the port, and (ii) to schedule available berths for the arriving vessels taking into account a multi-tidal planning horizon. In comparison with the state-of-the-art exact method using commercial solver and a competitive heuristic, the computational results prove our approach guarantees feasibility of solutions for all the problem instances and is able to find good solutions in a short amount of time, especially for large-scale instances. We also compare our results to an existing state-of-the-art Particle Swarm Optimisation and our work produces significantly better performances on all the test instances.
| Item Type: | Article |
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| Uncontrolled Keywords: | Levy flight, Berth allocation problem, Tidal windows, Meta-heuristic algorithms, Dynamic Optimisation |
| Subjects: | H Social Sciences > HE Transportation and Communications T Technology > TC Hydraulic engineering. Ocean engineering |
| Divisions: | Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20) |
| Publisher: | Elsevier |
| Date Deposited: | 26 Oct 2018 08:29 |
| Last Modified: | 04 Sep 2021 09:59 |
| DOI or ID number: | 10.1016/j.swevo.2018.10.011 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/9548 |
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