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Abstract

Berth Allocation Problem (BAP) is a renowned difficultcombinatorial optimization problemthat plays acrucial role in maritime transportation systems. BAP is categorizedas non-deterministic polynomial-time hard (NP-hard) problems, thatis very toughto resolveforoptimality within an acceptabletimeframe. Many metaheuristic algorithms have been suggestedto tacklethis problem, and yet, mostof these algorithms have some drawbacks such as theyhave a weak ability to explore the solutionspace (they struggleescaping fromlocal minima) and they face the difficulties to operate on different datasets. Consequently, the need to either enhance the existing algorithms or utilize a newalgorithm is still necessary. Harmony Search Algorithm(HSA) is one ofthe recentpopulation-based optimization methodswhichinspired by modern-nature. HSA has confirmed its ability to tackle various difficult combinatorial optimization problems likevehicle routing, exam timetablingto name a few. However, as far as we areconcerned, it has never been applied to tacklethe BAP problem. The primary objective of this articleis to examinethe effectiveness of HSA in solving BAP by identifying suitable values for the parameters of the HSA and then applying HSA to tackle BAP. Therefore, in this article, the basic HSA is proposedto tackle the BAP. The suggested HSA is tested on BAP benchmark (I3 dataset) and compared the results with other latest algorithms found in the literature.The trial outcomesevidenced that the HSA is promising, competitive, and that it has surpassed some other algorithms that have solved the same dataset, and the results were very near to the best-known results. Experimental results also prove the suitability and applicability of HSA in tackling the BAP

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