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Multi-objective hybrid genetic algorithm for quay crane dynamic assignment in berth allocation planning

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Abstract

The development of containers’ transportation has maintained a high momentum since 1961, especially, the containers’ traffic growth reached 10–11% in recent years. Container terminals play an important role in the transportation chain, in order to response rapidly for the requirement of modern logistics, better resource allocation, lower cost, and higher operation efficiency are needed. In this paper, we introduce the quay crane dynamic assignment (QCDA) in berth allocation planning problem (BAP) and formulate a multi-objective mathematical model considering each berth for container ship with QCDA and number of Quay Crane’s Move. In order to solve this QCDA in BAP problem, we propose a multi-objective hybrid Genetic Algorithm 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.

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Authors and Affiliations

  1. Logistics Research Center, Shanghai Maritime University, 200135, Shanghai, China

    Chengji Liang

  2. Business School, Shanghai University for Science and Technology, 200093, Shanghai, China

    Jianquan Guo

  3. Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, 8080135, Japan

    Yang Yang

Authors
  1. Chengji Liang
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  2. Jianquan Guo
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  3. Yang Yang
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Correspondence to Chengji Liang.

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Liang, C., Guo, J. & Yang, Y. Multi-objective hybrid genetic algorithm for quay crane dynamic assignment in berth allocation planning. J Intell Manuf 22, 471–479 (2011). https://doi.org/10.1007/s10845-009-0304-8

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  • DOI: https://doi.org/10.1007/s10845-009-0304-8

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