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Berth and quay crane coordinated scheduling using multi-objective chaos cloud particle swarm optimization algorithm

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Abstract

The demand for the maritime transportation has significantly increased over the past 20 years due to the rapid pace of globalization. Terminal managers confront the challenge in establishing the appropriate berth and quay crane (QC) coordinated schedule to achieve the earliest departure time of ship and to provide efficient service. In this paper, we propose a multi-objective berth and QC coordinated scheduling model, namely M-B&QC, by taking the minimum additional trucking distance and the port time of ships as the optimization objectives, with the constraints based on demand of port operations and vessel berthing. To solve the M-B&QC model, the particle coding rule and the particle feasible-integer processing module (namely PF-IP) for improving PSO performance are employed to determine the computation strategies of individual historical optimal value \(p_{i}^{G}\) and global optimal value \(P_{g}^{G}\) of particle for the multi-objective optimization. In addition, the global disturbance with cat mapping function (namely GDCM) and local search with cloud model (namely LSCM) are also hybridized, namely PM&CCPSO algorithm, to solve the M-B&QC model. Numerical experiments including eight combined examples are conducted to test the performance of the proposed programming model and the modified solving algorithm.

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Acknowledgments

The work is supported by the National Natural Science Foundation of China(51509056), the Postdoctoral Science Foundation of China (2015M571394), the Heilongjiang Postdoctoral Fund (LBH-Z14059), the Fundamental Research Funds for the Central Universities (HEUCF150108), Science and Technology Project of Western Transportation Construction of Ministry of Communications (2014364554050), and Ministry of Science and Technology, Taiwan (MOST 104-2410-H-161-002).

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Authors and Affiliations

  1. College of Shipbuilding Engineering, Harbin Engineering University, Harbin, 150001, Heilongjiang, China

    Ming-Wei Li, Jing Geng & Jianlun Wang

  2. Department of Information Management, Oriental Institute of Technology, 58, Sec. 2, Sichuan Rd., Panchiao, 220, New Taipei, Taiwan

    Wei-Chiang Hong

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  1. Ming-Wei Li
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  2. Wei-Chiang Hong
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  4. Jianlun Wang
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Correspondence to Wei-Chiang Hong.

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Li, MW., Hong, WC., Geng, J. et al. Berth and quay crane coordinated scheduling using multi-objective chaos cloud particle swarm optimization algorithm. Neural Comput & Applic 28, 3163–3182 (2017). https://doi.org/10.1007/s00521-016-2226-7

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  • DOI: https://doi.org/10.1007/s00521-016-2226-7

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