煤炭码头船货匹配下泊位动态分配多目标优化模型及算法

doi:10.12005/orms.2022.0003

运筹与管理 ›› 2022, Vol. 31 ›› Issue (1): 14-21.DOI: 10.12005/orms.2022.0003

煤炭码头船货匹配下泊位动态分配多目标优化模型及算法

邰世文¹, 商剑平¹, 饶卫振²

1.中交水运规划设计院有限公司,北京 100007;
2.山东科技大学经济管理学院,山东青岛 266590

收稿日期:2019-07-02 出版日期:2022-01-25 发布日期:2022-02-11
通讯作者: 饶卫振(1981-),男,博士生导师,教授,研究方向:物流系统优化。
基金资助:
泰山学者工程专项经费资助(tsqn201909111);教育部人文社科基金资助项目(21YJA630075,20YJCZH175);山东省社会科学基金(20CGLG32);山东省高等学校青创团队(2019RWG010)

Multi-objective Optimization Model and Genetic Algorithm for Dynamic Berth Allocation Problem under Cargo Matching in Coal Terminals

TAI Shi-wen¹, SHANG Jian-ping¹, RAO Wei-zhen²

1. CCCC Water Transportation Consultants Co., Ltd, Beijing 100007, China;
2. College of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China

Received:2019-07-02 Online:2022-01-25 Published:2022-02-11

摘要/Abstract

摘要： 本文针对输出型煤炭码头船货匹配下泊位动态分配问题,构建了堆场-取装线-泊位-船舶联合分配优化数学模型,并设计了采用仿真推演策略解码的遗传算法求解。首先,综合考虑船舶、泊位、堆场、取装线、煤种、航道开放时间和装船作业规则等要素,以船舶在港时间最短和作业效率最大为目标建立了相应的多约束多目标优化模型。然后,综合多目标优化、遗传算法以及仿真推演技术,设计了相应的遗传算法求解,包括:组合式编码、采用仿真推演策略的解码方法,追加了具有合法性检查的染色体生成算法,设计了采用多种策略的遗传操作等。最后实例表明,本算法的执行效率高而且优化效果好。

关键词: 煤炭码头, 泊位分配, 多目标优化, 仿真推演, 遗传算法

Abstract: This paper puts forward a co-optimization of stocks-reclaiming and loading lines-berths-vessels model on dynamic berth allocation problem under cargo matching in coal terminals and the genetic algorithm in which a simulation and deduction strategy is used to decode. First, the multi-constrained and multi-objective optimization model is established with the multi-objective concerning minimizing the total time of vessels in the port and maximizing the rate of loading and some constraints including vessels, berths, stocks, reclaiming and loading lines, coals, loading principles and so on. Then, on the basis of summing up multi-objective optimization, genetic algorithm and simulation-deduction techniques, the genetic algorithm is designed including the improved coding and decoding with the simulation and deduction method, the way of chromosome generation with validity checking, the design of fitness, genetic operation and correction using multiple strategies. Finally, the actual numerical experiments and the successful application have shown that the solution has a high execution efficiency and satisfactory effect.

Key words: coal terminal, berth allocation problem, multi-objective optimization, simulation and deduction, genetic algorithm

中图分类号:

U691+.31

邰世文, 商剑平, 饶卫振. 煤炭码头船货匹配下泊位动态分配多目标优化模型及算法[J]. 运筹与管理, 2022, 31(1): 14-21.

TAI Shi-wen, SHANG Jian-ping, RAO Wei-zhen. Multi-objective Optimization Model and Genetic Algorithm for Dynamic Berth Allocation Problem under Cargo Matching in Coal Terminals[J]. Operations Research and Management Science, 2022, 31(1): 14-21.

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煤炭码头船货匹配下泊位动态分配多目标优化模型及算法

Multi-objective Optimization Model and Genetic Algorithm for Dynamic Berth Allocation Problem under Cargo Matching in Coal Terminals

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