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检修期三峡-葛洲坝枢纽船舶过闸调度建模与优化OACHSSCDCSTPCD

Modeling and Optimization of Lockage Scheduling for Three Gorges-Gezhouba Dam During Maintenance Periods

中文摘要英文摘要

为解决三峡-葛洲坝枢纽船闸检修期船舶待闸时间过长、通过效率低等问题,根据检修期三峡-葛洲坝枢纽调度要求,建立船闸检修期三峡-葛洲坝枢纽船舶过闸调度模型,将船舶过闸调度问题分解为闸室编排、船闸分配、时间表优化 3个子问题.根据模型特性,分别构建Bottom-Left算法、考虑通航均衡的闸次分配算法和基于自适应秃鹰搜索的时间表优化算法对子问题依次进行求解.在检修期船舶过闸调度问题中,根据待闸船舶拥堵情况分为动态调度与静态调度两类场景进行分析.最后,以三峡-葛洲坝梯级枢纽通航的实际历史数据为例,将改进前后秃鹰搜索算法的优化结果进行比较.结果显示,一个调度周期内,船舶平均待闸时间可减少 3h左右,平均闸室面积利用率可达75%以上,船舶通过量可提升6艘.

To address problems such as long waiting time for ships and low passage efficiency during maintenance periods of the Three Gorges-Gezhouba Dam lock,a lockage scheduling model is developed according to the scheduling requirements of the Three Gorges-Gezhouba Dam lock.The lockage scheduling problem is decomposed into three subproblems:chamber arrangement,lockage assignment and timetable optimization.According to the characteristics of the model,the Bottom-Left algorithm,the lockage assignment algorithm considering navigation equilibrium and the timetable optimization algorithm based on adaptive bald eagle search are established to solve the sub-problems,respectively.In such lockage scheduling problem during maintenance periods,two scenarios including dynamic and static scheduling are analyzed according to the congestion level of ships awaiting lockage.Finally,actual historical data of the navigation from the Three Gorges-Gezhouba dam lock are used for comparing the optimization results of the original and modified bald eagle search algorithms.Results show that in a scheduling cycle,the average waiting time of ships can be reduced by about three hours,the average utilization rate of lock chambers can reach over 75%,and the ship throughput can be increased by six ships.

梁晓磊;张东美;张煜;黄凯

武汉科技大学 汽车与交通工程学院,湖北 武汉 430065武汉理工大学 物流工程学院,湖北 武汉 430070

经济学

三峡-葛洲坝联合调度船闸检修期秃鹰搜索算法优化闸室编排船闸分配

Three Gorges-Gezhouba Damco-schedulinglock maintenance periodsbald eagle search algorithm optimizationlock chamber arrangementlockage assignment

《工业工程》 2024 (003)

43-53,86 / 12

国家自然科学基金面上资助项目(71874132)

10.3969/j.issn.1007-7375.220257

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