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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2018  >  18(3): 199-209
WU Di, WANG Nuo, LIN Wan-ni, WU Nuan. Alternate evolution algorithm based on plant growth simulation for berth-quay crane joint allocation model[J]. Journal of Traffic and Transportation Engineering, 2018, 18(3): 199-209. doi: 10.19818/j.cnki.1671-1637.2018.03.020
Citation: WU Di, WANG Nuo, LIN Wan-ni, WU Nuan. Alternate evolution algorithm based on plant growth simulation for berth-quay crane joint allocation model[J]. Journal of Traffic and Transportation Engineering, 2018, 18(3): 199-209. doi: 10.19818/j.cnki.1671-1637.2018.03.020
shu

Alternate evolution algorithm based on plant growth simulation for berth-quay crane joint allocation model

doi: 10.19818/j.cnki.1671-1637.2018.03.020

  • College of Transportation Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China

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  • Author Bio:

    WU Di(1989-), male, doctoral student, wudidlmu@163.com

    WANG Nuo(1954-), male, professor, PhD, wangnuodl@126.com

  • Received Date: 2018-01-07
  • Publish Date: 2018-06-25
    Abstract
  • To optimize the berth-quay crane joint allocation plans in a container terminal synthetically, the independence and system relevance between berth and quay crane were analysed. Based on the independence, two optimized sub-models were established, one to target the berth with the minimum average time in port, and the other to target the quay cranes with the minimum operating cost. Based on the system relevance, the constraint conditions for berth-quay crane joint allocation were constructed, the two sub-models were linked closely, and a complete berth-quay crane joint allocation model was established. The characteristics of the joint allocation model were analysed, and an alternate evolution algorithm based on plant growth simulation wasdesigned to solve it. Alternate evolution operators based on the plant growth simulation algorithm were used to alternately optimize the two targets of each individual in the population to achieve population evolution. The non-dominated solutions were screened through the algorithm framework. After multiple population evolutions and non-dominated solution screening, the Pareto satisfactory solution set for the berth-quay crane joint allocation was obtained. A berthquay crane joint allocation plan for 31 vessels arriving within 3 din the container terminal of Dalian Port was optimized and compared with the multi-objective genetic algorithm. Calculation result shows that 13 satisfactory solutions are obtained. The average vessel time in the port is 7.47-9.44 h, the number of quay cranes used is 85-96 and the total operating cost is 208 680-211 140 yuan. Compared with the optimization results of the multi-objective genetic algorithm, the computation speed is 6.07% faster, and four more non-dominated solutions are achieved with an increase rate of 30.76%, the results are closer to the Pareto frontier and the optimization degree of joint allocation plan is higher. The designed alternate evolution algorithm based on plant growth simulation maintains the maximized independence of an individual in the population evolution process and obtains more non-inferior solutions, and the alternate evolutionary approach provides results closer to the Pareto frontier.

     

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