|Table of Contents|

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

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2018年03期
Page:
199-209
Research Field:
交通运输规划与管理
Publishing date:

Info

Title:
Alternate evolution algorithm based on plant growth simulation for berth-quay crane joint allocation model
Author(s):
WU Di;  WANG Nuo;  LIN Wan-ni;  WU Nuan
College of Transportation Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China
Keywords:
shipping management;  container terminal;  berth-quay crane joint allocation;  alternate evolution algorithm based on plant growth simulation;  multi-objective optimization;  Pareto optimum
PACS:
U691.31
DOI:
-
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 was designed 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 berth-quay crane joint allocation plan for 31 vessels arriving within 3 d in 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. 3 tabs, 7 figs, 26 refs.

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Last Update: 2018-07-14