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Multiobjective hybrid genetic algorithm for quay crane scheduling in berth allocation planning

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  • Chengji Liang
  • Lin Lin
  • Jungbok Jo

Abstract

With the development of the global business and logistics under the internet environment a Container Terminal (CT) system becomes more and more busy. Therefore, the available resources in the seaport get scarcer than before. In order to increase the operating efficiency of CT system, the resources planning problem has become a critical issue in the fields of operations research and logistics. In this paper, we introduce the Berth Allocation Planning (BAP) problem and formulate a multiobjective mathematical model considering each berth for container ship with different number of Quay Cranes (QCs) and balance of QC's workload. In order to solve this QC scheduling in BAP problem, we propose a multiobjective hybrid Genetic Algorithm (mohGA) approach with a priority-based encoding method. To demonstrate the effectiveness of proposed mohGA approach, numerical experiment is carried out and the best solution to the problem is obtained.

Suggested Citation

  • Chengji Liang & Lin Lin & Jungbok Jo, 2009. "Multiobjective hybrid genetic algorithm for quay crane scheduling in berth allocation planning," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 16(1/2), pages 127-146.
    • Handle: RePEc:ids:ijmtma:v:16:y:2009:i:1/2:p:127-146
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    Cited by:

    1. 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.
    2. 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.

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