集装箱港口多码头泊位联合分配优化研究  

Optimization of integrated allocation of multiterminal's berths in container port

作　　者：张艳伟[1,2] 王楠 朱凌坤[1] ZHANG Yanwei;WANG Nan;ZHU Lingkun(School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan 430063,Hubei,China;State Key Laboratory of Maritime Technology and Safety,Wuhan 430063,Hubei,China)

机构地区：[1]武汉理工大学交通与物流工程学院,湖北武汉430063 [2]水路交通控制全国重点实验室,湖北武汉430063

出　　处：《中国工程机械学报》2024年第3期293-298,共6页Chinese Journal of Construction Machinery

基　　金：新一代人工智能国家科技重大专项(2022ZD0119303)。

摘　　要：多码头泊位联合分配是港口资源整合、提升服务水平的重要手段。针对集装箱港口多码头泊位计划,考虑不同码头泊位条件、岸桥能力等因素,构建多码头泊位-岸桥集成分配数学模型。设计改进灰狼算法(IGWO),利用离散化映射进行编码设计,基于优胜劣汰法实现种群动态进化。设计算例,将IGWO与果蝇算法和粒子群算法进行对比。结果显示:IGWO算法优化结果分别提升16.6%和21.1%;利用IGWO对不同船舶到港密度泊位算例进行求解,其中,多码头泊位分配可有效减少总时间成本及延误船舶数量,节省岸线资源约10%。结果表明:设计的模型及算法可有效解决多码头泊位联合分配问题。Integrated allocation of multi-terminal berths is an important means to integrate port resources and improve service level.According to the multi-terminal berth plan of container port,considering the factors such as different terminal berth conditions,quay crane capacity,etc.,the integrated allocation mathematical model of multi-terminal berth and quay crane is constructed.The improved grey wolf algorithm(IGWO) is designed,the discrete mapping method is used for coding design,and the population dynamic evolution is realized based on the survival of the fittest rule.An example is designed to compare IGWO with drosophila algorithm and particle swarm optimization algorithm.The results show that the optimization results of IGWO algorithm increase by 16.6% and 21.1% respectively;IGWO is used to solve different ship arrival density examples.Among them,multi-terminal berth allocation can effectively reduce the total cost of time and the number of delayed ships,saving about 10% of shoreline.The research shows that the designed model and algorithm can effectively solve the joint allocation problem of multi-terminal berths.

关 键 词：集装箱港口 多码头资源分配 泊位计划 泊位-岸桥集成分配 灰狼算法 

分 类 号：U695.22[交通运输工程—港口、海岸及近海工程]