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Multi-objective and prioritized berth allocation in container ports

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  • C. Cheong
  • K. Tan
  • D. Liu
  • C. Lin

Abstract

This paper considers a berth allocation problem (BAP) which requires the determination of exact berthing times and positions of incoming ships in a container port. The problem is solved by optimizing the berth schedule so as to minimize concurrently the three objectives of makespan, waiting time, and degree of deviation from a predetermined priority schedule. These objectives represent the interests of both port and ship operators. Unlike most existing approaches in the literature which are single-objective-based, a multi-objective evolutionary algorithm (MOEA) that incorporates the concept of Pareto optimality is proposed for solving the multi-objective BAP. The MOEA is equipped with three primary features which are specifically designed to target the optimization of the three objectives. The features include a local search heuristic, a hybrid solution decoding scheme, and an optimal berth insertion procedure. The effects that each of these features has on the quality of berth schedules are studied. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • C. Cheong & K. Tan & D. Liu & C. Lin, 2010. "Multi-objective and prioritized berth allocation in container ports," Annals of Operations Research, Springer, vol. 180(1), pages 63-103, November.
    • Handle: RePEc:spr:annopr:v:180:y:2010:i:1:p:63-103:10.1007/s10479-008-0493-0
    DOI: 10.1007/s10479-008-0493-0
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    References listed on IDEAS

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    Cited by:

    1. H. L. Ma & S. H. Chung & H. K. Chan & Li Cui, 2019. "An integrated model for berth and yard planning in container terminals with multi-continuous berth layout," Annals of Operations Research, Springer, vol. 273(1), pages 409-431, February.
    2. Bierwirth, Christian & Meisel, Frank, 2015. "A follow-up survey of berth allocation and quay crane scheduling problems in container terminals," European Journal of Operational Research, Elsevier, vol. 244(3), pages 675-689.
    3. Lalla-Ruiz, Eduardo & Expósito-Izquierdo, Christopher & Melián-Batista, Belén & Moreno-Vega, J. Marcos, 2016. "A Set-Partitioning-based model for the Berth Allocation Problem under Time-Dependent Limitations," European Journal of Operational Research, Elsevier, vol. 250(3), pages 1001-1012.
    4. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2012. "Multi-objective optimization for stochastic computer networks using NSGA-II and TOPSIS," European Journal of Operational Research, Elsevier, vol. 218(3), pages 735-746.
    5. Imai, Akio & Nishimura, Etsuko & Papadimitriou, Stratos, 2013. "Marine container terminal configurations for efficient handling of mega-containerships," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 141-158.
    6. Robenek, Tomáš & Umang, Nitish & Bierlaire, Michel & Ropke, Stefan, 2014. "A branch-and-price algorithm to solve the integrated berth allocation and yard assignment problem in bulk ports," European Journal of Operational Research, Elsevier, vol. 235(2), pages 399-411.
    7. Xu, Jiuping & Song, Xiaoling & Wu, Yimin & Zeng, Ziqiang, 2015. "GIS-modelling based coal-fired power plant site identification and selection," Applied Energy, Elsevier, vol. 159(C), pages 520-539.
    8. Arijit De & Saurabh Pratap & Akhilesh Kumar & M. K. Tiwari, 2020. "A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach," Annals of Operations Research, Springer, vol. 290(1), pages 783-811, July.
    9. Adrián Ramírez-Nafarrate & Rosa G. González-Ramírez & Neale R. Smith & Roberto Guerra-Olivares & Stefan Voß, 2017. "Impact on yard efficiency of a truck appointment system for a port terminal," Annals of Operations Research, Springer, vol. 258(2), pages 195-216, November.
    10. Xu, Dongsheng & Li, Chung-Lun & Leung, Joseph Y.-T., 2012. "Berth allocation with time-dependent physical limitations on vessels," European Journal of Operational Research, Elsevier, vol. 216(1), pages 47-56.
    11. Abdellah Salhi & Ghazwan Alsoufi & Xinan Yang, 2019. "An evolutionary approach to a combined mixed integer programming model of seaside operations as arise in container ports," Annals of Operations Research, Springer, vol. 272(1), pages 69-98, January.
    12. Lotte Berghman & Roel Leus & Frits Spieksma, 2014. "Optimal solutions for a dock assignment problem with trailer transportation," Annals of Operations Research, Springer, vol. 213(1), pages 3-25, February.
    13. Song, Xiaoling & Xu, Jiuping & Zhang, Zhe & Shen, Charles & Xie, Heping & Peña-Mora, Feniosky & Wu, Yimin, 2017. "Reconciling strategy towards construction site selection-layout for coal-fired power plants," Applied Energy, Elsevier, vol. 204(C), pages 846-865.
    14. Eduardo Lalla-Ruiz & Stefan Voß & Christopher Expósito-Izquierdo & Belén Melián-Batista & J. Marcos Moreno-Vega, 2017. "A POPMUSIC-based approach for the berth allocation problem under time-dependent limitations," Annals of Operations Research, Springer, vol. 253(2), pages 871-897, June.
    15. Umang, Nitish & Bierlaire, Michel & Vacca, Ilaria, 2013. "Exact and heuristic methods to solve the berth allocation problem in bulk ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 54(C), pages 14-31.
    16. Shangyao Yan & Chung-Cheng Lu & Jun-Hsiao Hsieh & Han-Chun Lin, 2019. "A Dynamic and Flexible Berth Allocation Model with Stochastic Vessel Arrival Times," Networks and Spatial Economics, Springer, vol. 19(3), pages 903-927, September.
    17. Imai, Akio & Yamakawa, Yukiko & Huang, Kuancheng, 2014. "The strategic berth template problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 77-100.

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