集装箱码头泊位作业系统统计分析与评价
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摘要
随着现代物流的不断发展,码头管理者越来越意识到提高码头作业系统的运作效率是增强码头竞争力的关键因素,集装箱码头作业系统已成为研究的热点之一泊位作业系统是集装箱码头作业系统的一个重要的组成部分,是货物在水陆间转运的核心环节,提高泊位系统的作业效率能极大的提高码头的服务质量和作业效率。泊位作业系统主要包括以下实体：泊位、到港船舶和负责装卸的岸桥,货物转运的过程就是在这几方面实体的互动过程中完成的。选择合适的作业方式会极大的缩短船舶在港时间,提高泊位、岸桥的利用率,进而提高码头的作业效率,提高码头自身的竞争力,因此对泊位作业系统进行研究具有重要的现实意义。
本文考虑了离散型与连续型两种泊位作业系统,对这两种泊位系统进行模拟仿真并进行统计分析与评价,进而对两种泊位系统进行对比分析。主要考虑泊位指派方式、为到港船舶服务方式以及岸桥分配方式三个因素对泊位系统的影响,建立了指标体系评价泊位系统的作业效率。评价指标体系主要包括泊位利用率、岸桥利用率、船舶作业率以及船舶平均等待时间四个指标。然后用蒙特卡罗法对泊位作业系统进行模拟仿真,对得到的数据进行统计分析,得出在不同的作业条件下各指标值的差异。根据各因素单独变化以及同时变化时指标值的差异得出各因素对泊位系统的影响程度及各种方式的优劣,从而选出在码头规模一定的情况下,泊位指派、到港船舶服务方式及作业岸桥数量相互配合的最优的作业方式,能够对港航企业的运作起到一定的辅助指导与决策支持作用。
With the development of modern logistics, port managers are increasingly aware of the importance of improving terminal operation efficiency of logistics. Container terminal operation system has become the hotspot to research. Berth assignment system is an important part of container terminal. Improving the efficiency of berth assignment system can greatly improve the service quality and the operation efficiency of port. The designated ways of berth, the service strategies for vessels, and the allocation ways of quay crane are the important factors to improve the operation efficiency of port and the operation efficiency of vessel. So researching the berth assignment system has important practical significance.
The thesis considers two kinds of berth circumstances which are the discrete berth and the continuous berth. The berth system is simulated and statistically analyzed and evaluated. Firstly establish the evaluation index system to describe the designated ways of berth, the service strategies for vessels and the allocation ways of quay crane. The evaluation index system mainly includes four indices which are berth utilization rate, quay crane utilization rate, the vessel average waiting time and the vessel operation rate. Then use Monte-Carlo method to simulate the different operation ways and gain the simulation data of the index values. And analyze the data by using the variance analysis and sensitivity analysis. Lastly present the optimal operation way of berth assignment system according to the differences of index values. The optimal operation way will help the operators of the port to make a correct decision.
本文考虑了离散型与连续型两种泊位作业系统,对这两种泊位系统进行模拟仿真并进行统计分析与评价,进而对两种泊位系统进行对比分析。主要考虑泊位指派方式、为到港船舶服务方式以及岸桥分配方式三个因素对泊位系统的影响,建立了指标体系评价泊位系统的作业效率。评价指标体系主要包括泊位利用率、岸桥利用率、船舶作业率以及船舶平均等待时间四个指标。然后用蒙特卡罗法对泊位作业系统进行模拟仿真,对得到的数据进行统计分析,得出在不同的作业条件下各指标值的差异。根据各因素单独变化以及同时变化时指标值的差异得出各因素对泊位系统的影响程度及各种方式的优劣,从而选出在码头规模一定的情况下,泊位指派、到港船舶服务方式及作业岸桥数量相互配合的最优的作业方式,能够对港航企业的运作起到一定的辅助指导与决策支持作用。
With the development of modern logistics, port managers are increasingly aware of the importance of improving terminal operation efficiency of logistics. Container terminal operation system has become the hotspot to research. Berth assignment system is an important part of container terminal. Improving the efficiency of berth assignment system can greatly improve the service quality and the operation efficiency of port. The designated ways of berth, the service strategies for vessels, and the allocation ways of quay crane are the important factors to improve the operation efficiency of port and the operation efficiency of vessel. So researching the berth assignment system has important practical significance.
The thesis considers two kinds of berth circumstances which are the discrete berth and the continuous berth. The berth system is simulated and statistically analyzed and evaluated. Firstly establish the evaluation index system to describe the designated ways of berth, the service strategies for vessels and the allocation ways of quay crane. The evaluation index system mainly includes four indices which are berth utilization rate, quay crane utilization rate, the vessel average waiting time and the vessel operation rate. Then use Monte-Carlo method to simulate the different operation ways and gain the simulation data of the index values. And analyze the data by using the variance analysis and sensitivity analysis. Lastly present the optimal operation way of berth assignment system according to the differences of index values. The optimal operation way will help the operators of the port to make a correct decision.
引文
[1]Lai K K,Shih K. A study of container berth allocation[J]. Journal of Advanced Transportion,1992,26:45-60.
[2]Imai A, Nagaiwa K,Chan C W. Efficient planning of berth allocation for container terminals in Asia[J]. Journal of Advanced Transportation,1997,31(1):75-94.
[3]Imai A, Nishimura E, Papadimitriou S. The dynamic berth allocation problem for a container port [J]. Transportation Research B,2001,35:401-417.
[4]Li C L, Cai X, Lee C Y. Seheduling with multiple-job-on-processor pattern. HE Transactions,1998,30:433-445.
[5]Nishimura E, Imai A, Papadimitriou S. Berth allocation planning in the public berth system by genetic algorithms[J]. European Journal of Operational Research,2001,131(2):282-292.
[6]Lim A. The berth planning problem [J]. Operations Research Letters, 1998,22(223):105-110.
[7]Guan Y, Xiao W Q, Cheng R K, Li C L. A multiprocessor task scheduling model for berth allocation heuristic and worst-case analysis. Operations Research Letters,2002(30): 343-350.
[8]黄晓鸣,徐小义,排队论在港口规划设计中的应用,青岛大学学报,1996(03).
[9]鲁子爱,港口服务系统仿真与港口规模优化研究：(博士学位论文),南京：河海大学,2002(4).
[10]周鹏飞,面向不确定环境的集装箱码头优化调度研究：(博士学位论文),大连：大连理工大学,2005(10).
[11]刘义发,郭创豪.最佳泊位利用率的计算方法.珠江水运,2006,9：41-43.
[12]唐臣.基于随机Petri网的集装箱码头通过能力系统仿真[D].大连理工大学,2006.
[13]李巍.集装箱码头物流系统仿真与优化研究[D].大连理工大学,2006.
[14]Imai A, Chen H C,Nishimura E. The simultaneous berth and quay crane allocation problem [J]. Transportation Research Part E:Logistics and Transportation Review,2008, 44(5):900-920.
[15]Liang C, Huang Y, Yang Y. A quay crane dynamic scheduling problem by hybrid evolutionary algorithm for berth allocation planning[J]. Computers & Industrial Engineering,2009,56(3):10-12.
[16]Lee Y, Chen C Y. An optimization heuristic for the berth scheduling problem[J]. European Journal of Operation Research,2009,196(2):500-508.
[17]Kozan E. Inceasing the operational efficiency of container terminals in Australia [J]. Journal of the Operational Research Society,1997,48(2):151-161.
[18]Kozan Erhan Comparison of analytical and simulation planning modals of seaport container terminals[J]. Transportation Planning and Technology,1997:235-248.
[19]Legato P, Mazza R M. Berth Planning and resources optimization at a container terminal via discrete event simulation[J]. European Journal of Operation Research Part B,1989:159-175.
[20]戈闻怡.集装箱港口作业物流资源配置的研究[D].上海海事大学,2003.
[21]蔡芸.港口集装箱物流系统仿真和优化方法的研究及应用[D].武汉理工大学.
[22]蔡芸,孙国止.同时求解泊位分配及岸桥调度问题的仿真优化方法[A].可持续发展的中国交通-2005全国博士生学术论坛(交通运输工程学科)论文集[C],2005.
[23]Erhan Kozan, Peter Preston. Genetic algorithms to schedule container transfers at multimodal teminals. International transactions in operational research,1999. (6).311-29.
[24]E. Kozan. Optimising Container Transfers at Multimodal Terminals. Mathematical and Computer Modelling,2000. (31),235-243.
[25]Brown G G, Law Phongpanich S, Thurman K P. Optimizing ship berthing. Naval Research Logistics,1994,41:1-15.
[26]Brown G G, Cormican K J, LaWPhongpanich S, Widdis D B. Optimizing submarine berthing with a Persistence incentive. Naval Research Logistics,1997,44:301-318.
[27]Chen C Y, Hsieh T W. A time space network model for the berth allocation problem.19th. IFIP TC6 Conference on System Modeling and Optimization, Cambridge, UK,1999,7.
[28]Daganzo C F. The crane seheduling problem. Transportation Researeh Part B,1989:159-175.
[29]Peterkofsky R I,Daganzo C F.A branch and bound solution method for the crane scheduling problem. Transportation Research PartB,1990:159-172.
[30]Park Y M, Kim K H. A scheduling method for berth and quay cranes[J]. OR Spectrum, 2003,25(1):12-23
[31]Park K T, Kim K M. Berth scheduling for container terminals by using a sub-gradient optimization technique[J]. Journal of the Operational Research Society,2002,53(9): 1054-1062.
[32]Haghani A, Kaisar E I.A model for designing container loading plans for containership Working paper, University of Maryland, Transportation Research Board 2001 Annual meeting,2001.
[33]Dubrovsky O, Levitin G, Penn M. A genetic algorithm with a compact solution encoding for the container ship stowage problem. Journal of Heuristies,2002.
[34]J.Bose, T. Reiners, D. Steenken, S.Voss. Vehicle dispatching at seaport container terminals using evolutionary algorithms, System Sciences,2000. Proceeding of the 33rd Annual Hawaii International Conference on, Jan.2000 vol 2:1-10.
[35]秦固.集装箱码头装卸效率计算及参数取值分析.港口装卸,2007,2：36-38.
[36]韩骏,孙晓娜,靳志宏.集装箱码头泊位与岸桥协调调度优化[J].大连海事大学学报.2008,34(2)：117-121.
[37]杨静蕾,丁以中.集装箱码头设备配置的模拟研究.系统仿真学报，2003.15(8).1069-1073.
[38]李冠声.上海港集装箱码头吞吐能力与设备配置优化.中国港口,2002.(8).25-26.
[39]秦永宏，陈强努,沙梅.港口集装箱装卸工艺系统的计算机仿真.计算机辅助工程,2000.(4).11-18
[40]M. Kia, E. Shayan, F.Ghotb. Investigation of port capacity under a new approach by computer simulation. Computers&Industrial Engineering,2002. (42).533-540.
[41]Nam K C, Kwak KS, Yu NS. Simulation study of container terminal performance Journal of Wateway Port Coastal and Ocean Engineering-Asee,2002.128(3).126-132.
[42]Mark B. Duinkerken, Joseph J. M. Evers, Jaap A. Ottjes. A simulation model for integrating quay transport and stacking policies on automated container terminals. Proeeedings of the European Simulation Multicongerence,2001.909-916.
[2]Imai A, Nagaiwa K,Chan C W. Efficient planning of berth allocation for container terminals in Asia[J]. Journal of Advanced Transportation,1997,31(1):75-94.
[3]Imai A, Nishimura E, Papadimitriou S. The dynamic berth allocation problem for a container port [J]. Transportation Research B,2001,35:401-417.
[4]Li C L, Cai X, Lee C Y. Seheduling with multiple-job-on-processor pattern. HE Transactions,1998,30:433-445.
[5]Nishimura E, Imai A, Papadimitriou S. Berth allocation planning in the public berth system by genetic algorithms[J]. European Journal of Operational Research,2001,131(2):282-292.
[6]Lim A. The berth planning problem [J]. Operations Research Letters, 1998,22(223):105-110.
[7]Guan Y, Xiao W Q, Cheng R K, Li C L. A multiprocessor task scheduling model for berth allocation heuristic and worst-case analysis. Operations Research Letters,2002(30): 343-350.
[8]黄晓鸣,徐小义,排队论在港口规划设计中的应用,青岛大学学报,1996(03).
[9]鲁子爱,港口服务系统仿真与港口规模优化研究：(博士学位论文),南京：河海大学,2002(4).
[10]周鹏飞,面向不确定环境的集装箱码头优化调度研究：(博士学位论文),大连：大连理工大学,2005(10).
[11]刘义发,郭创豪.最佳泊位利用率的计算方法.珠江水运,2006,9：41-43.
[12]唐臣.基于随机Petri网的集装箱码头通过能力系统仿真[D].大连理工大学,2006.
[13]李巍.集装箱码头物流系统仿真与优化研究[D].大连理工大学,2006.
[14]Imai A, Chen H C,Nishimura E. The simultaneous berth and quay crane allocation problem [J]. Transportation Research Part E:Logistics and Transportation Review,2008, 44(5):900-920.
[15]Liang C, Huang Y, Yang Y. A quay crane dynamic scheduling problem by hybrid evolutionary algorithm for berth allocation planning[J]. Computers & Industrial Engineering,2009,56(3):10-12.
[16]Lee Y, Chen C Y. An optimization heuristic for the berth scheduling problem[J]. European Journal of Operation Research,2009,196(2):500-508.
[17]Kozan E. Inceasing the operational efficiency of container terminals in Australia [J]. Journal of the Operational Research Society,1997,48(2):151-161.
[18]Kozan Erhan Comparison of analytical and simulation planning modals of seaport container terminals[J]. Transportation Planning and Technology,1997:235-248.
[19]Legato P, Mazza R M. Berth Planning and resources optimization at a container terminal via discrete event simulation[J]. European Journal of Operation Research Part B,1989:159-175.
[20]戈闻怡.集装箱港口作业物流资源配置的研究[D].上海海事大学,2003.
[21]蔡芸.港口集装箱物流系统仿真和优化方法的研究及应用[D].武汉理工大学.
[22]蔡芸,孙国止.同时求解泊位分配及岸桥调度问题的仿真优化方法[A].可持续发展的中国交通-2005全国博士生学术论坛(交通运输工程学科)论文集[C],2005.
[23]Erhan Kozan, Peter Preston. Genetic algorithms to schedule container transfers at multimodal teminals. International transactions in operational research,1999. (6).311-29.
[24]E. Kozan. Optimising Container Transfers at Multimodal Terminals. Mathematical and Computer Modelling,2000. (31),235-243.
[25]Brown G G, Law Phongpanich S, Thurman K P. Optimizing ship berthing. Naval Research Logistics,1994,41:1-15.
[26]Brown G G, Cormican K J, LaWPhongpanich S, Widdis D B. Optimizing submarine berthing with a Persistence incentive. Naval Research Logistics,1997,44:301-318.
[27]Chen C Y, Hsieh T W. A time space network model for the berth allocation problem.19th. IFIP TC6 Conference on System Modeling and Optimization, Cambridge, UK,1999,7.
[28]Daganzo C F. The crane seheduling problem. Transportation Researeh Part B,1989:159-175.
[29]Peterkofsky R I,Daganzo C F.A branch and bound solution method for the crane scheduling problem. Transportation Research PartB,1990:159-172.
[30]Park Y M, Kim K H. A scheduling method for berth and quay cranes[J]. OR Spectrum, 2003,25(1):12-23
[31]Park K T, Kim K M. Berth scheduling for container terminals by using a sub-gradient optimization technique[J]. Journal of the Operational Research Society,2002,53(9): 1054-1062.
[32]Haghani A, Kaisar E I.A model for designing container loading plans for containership Working paper, University of Maryland, Transportation Research Board 2001 Annual meeting,2001.
[33]Dubrovsky O, Levitin G, Penn M. A genetic algorithm with a compact solution encoding for the container ship stowage problem. Journal of Heuristies,2002.
[34]J.Bose, T. Reiners, D. Steenken, S.Voss. Vehicle dispatching at seaport container terminals using evolutionary algorithms, System Sciences,2000. Proceeding of the 33rd Annual Hawaii International Conference on, Jan.2000 vol 2:1-10.
[35]秦固.集装箱码头装卸效率计算及参数取值分析.港口装卸,2007,2：36-38.
[36]韩骏,孙晓娜,靳志宏.集装箱码头泊位与岸桥协调调度优化[J].大连海事大学学报.2008,34(2)：117-121.
[37]杨静蕾,丁以中.集装箱码头设备配置的模拟研究.系统仿真学报，2003.15(8).1069-1073.
[38]李冠声.上海港集装箱码头吞吐能力与设备配置优化.中国港口,2002.(8).25-26.
[39]秦永宏，陈强努,沙梅.港口集装箱装卸工艺系统的计算机仿真.计算机辅助工程,2000.(4).11-18
[40]M. Kia, E. Shayan, F.Ghotb. Investigation of port capacity under a new approach by computer simulation. Computers&Industrial Engineering,2002. (42).533-540.
[41]Nam K C, Kwak KS, Yu NS. Simulation study of container terminal performance Journal of Wateway Port Coastal and Ocean Engineering-Asee,2002.128(3).126-132.
[42]Mark B. Duinkerken, Joseph J. M. Evers, Jaap A. Ottjes. A simulation model for integrating quay transport and stacking policies on automated container terminals. Proeeedings of the European Simulation Multicongerence,2001.909-916.