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Novel wharf-based genetic algorithm for berth allocation planning

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Abstract

Commercial ports require an efficient means of scheduling vessels for public berths. In this study, a wharf-based genetic algorithm is proposed for the scheduling of public berths with the aim of reducing reliance on communications and shortening the waiting time of vessels. Schedules are initially encoded as chromosomes, based on wharf characteristics and the need from the generated wharf matching lists to avoid assigning vessels to inappropriate wharves. The proposed algorithm uses a special wharf-based sequential type of chromosome that keeps all of the generated schedules as feasible solutions. Following the selection process, crossover, and mutation, the proposed algorithm adjusts the usage of wharves in order to increase the speed of convergence. The proposed algorithm is able to handle a greater number of vessels when combined with the map-reduce technique. Experimental results demonstrate the effectiveness of the proposed algorithm at assigning vessels to appropriate berths as soon as they arrive. Compared to three other existing algorithms, it performs nine times faster in terms of convergence speed and produces better quality of the solutions.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan

    An-Hsiou Tsai, Chung-Nan Lee, Jain-Shing Wu & Fu-Sheng Chang

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  1. An-Hsiou Tsai
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  2. Chung-Nan Lee
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  3. Jain-Shing Wu
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  4. Fu-Sheng Chang
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Correspondence to Chung-Nan Lee.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by C.-H. Chen.

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Tsai, AH., Lee, CN., Wu, JS. et al. Novel wharf-based genetic algorithm for berth allocation planning. Soft Comput 21, 2897–2910 (2017). https://doi.org/10.1007/s00500-016-2272-1

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  • DOI: https://doi.org/10.1007/s00500-016-2272-1

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