基于Agent的集装箱码头实时调度系统的研究
|
摘要
集装箱码头实时调度是在无线通讯、移动终端、分布式数据处理等信息技术在集装箱码头应用普及的基础上发展起来的一种新的作业调度模式,相对于传统调度模式更有助于提高码头作业效率和资源利用率。
集装箱码头资源优化与调度研究涉及管理学、运筹学、信息科学、港口工程等许多相关领域的研究,本文研究的集装箱码头实时调度系统也是多种理论和技术的集成应用体。通过本文研究将对集装箱码头的调度体系和理论、组合优化理论、对多Agent和移动Agent应用框架和机制在集装箱码头生产作业中的应用、完善和推广起到积极的作用。本文采用基于AUML的面向Agent分析方法设计了集装箱码头实时调度系统的功能和交互模型。应用这种模型对进一步提高码头生产资源的利用率,加强生产作业环节的协作性,提高码头作业效率和吞吐能力,对提高码头应对突发事件的响应能力,保障码头作业连续性、稳定性及提高客户满意度等均有现实意义。
本文完成的主要研究工作包括：
(1)研究了基于Agent的集装箱码头实时调度框架模型。
本文基于AUML的AOA方法,逐步设计了集装箱码头实时调度系统的角色行为模型、结构框架模型和交互模型,从宏观的角度分析了实时调度系统的功能,各功能间的关系以及协同工作的交互方式,给出了系统的框架模型。
(2)进行了面向实时调度的智能计划Agent设计。
主要研究了面向实时调度的、支持动态调整的、智能的生产计划编制方法。结合Agent的功能结构,较为详细地设计了泊位岸桥计划Agent、单船计划Agent、资源配置计划Agent的功能模型,提出了相关的优化算法。论文中还总结了各Agent如何协同工作实现针对现场突发事件的实时调度以及Agent环境数据获取的优化方法。
(3)设计了基于移动Agent技术的岸桥-集卡-场桥协同作业的实时调度模型。
本文通过引入移动Agent技术,重点研究其移动机制、移动策略、通信机制等关键问题,充分利用移动Agent能够节约网络带宽、克服网络延迟、支持异步自主执行、具有动态适应性、增强应用的鲁棒性和容错能力等技术优势,设计出了现场岸桥-集卡-场桥协同作业模型,提高了实时调度系统及时响应能力和鲁棒性。
总体来讲,本文通过针对集装箱码头实时调度系统的模型设计,并用实例论述了模型对“边装边卸”、“重来重去”等有实时调度特色的作业模式的支持,能够为将来全面设计开发集装箱码头实时调度系统提供了一套较为全面的参考模型。
As wireless communication, mobile terminal, distributed data processing information technology in container terminal is becoming more and more popular, a new kind of Container Terminal Scheduling model of Real-time is put forward. Compared with the traditional scheduling model it is more useful to improve efficiency of resource utilization and terminal operation. The researches on Container terminal resources optimization and dispatching management involve management, operations research, information science, port engineering and many related fields. So Container terminal real-time scheduling system is the integration of theory and application of technology. The study in this thesis can play an active role in the application, perfection, popularization of the theory of container terminal operation system, the theory of combinatorial optimization, application framework of Mulit-Agent and Mobile-Agent. Based on Agent Oriented Analysis using AUML, the function and interactive model of container terminal real-time scheduling system were designed in this thesis. Applying this model to further improve the utilization of productive resources, to strengthen cooperation between operations, to improve the working efficiency and throughput capacity of wharf, to guarantee the stability and continuity of terminal operations, to improve customer satisfaction has practical significance.
Mainly studies completed in the paper include:
(1) Researched on real-time scheduling framework model based on Agent
Based on the method of AUML AOA, the Role-Active model, the Structural Framework Model, and the interactive model were designed. These models analyzed the functions, the relation between functions and the interactive mode in Real-time scheduling system from the macroscopic Angle, and all these models macroscopic Angle made up system framework model.
(2) Designed Real-time scheduling oriented intelligent Plan Agents
Real-time oriented, supporting dynamic adjustment, intelligent operation planning methods were studied. In this thesis Berth-crane plan Agent model, Ship plan Agent model, Machine plan Agent model were designed in detail. And relevant optimization algorithms were put forward. The thesis also summarized how Agents collaborative work to realize real-time scheduling for emergency, and optimization methods of acquiring Agent environmental data.
(3) Designed Real-time operation model by cooperation with shore crane, truck based on Mobile-Agent technology
Mobile-Agent technology has many advantages such as save network bandwidth, overcome the network latency, support asynchronous independent execution, with dynamic adaptability, enhance application robustness and tolerance, etc. These advantages are very important for real-time scheduling in wireless-network environment. The thesis provided a real-time operation model based on mobile-agent and give the detail explanation of architecture and working mechanism, discuss the key technology in design and implementation. This model can reduce influence of the quality of wireless network communication on system, improve the system response ability and offer a new method to implement real-time dispatcher in container terminal.
Generally speaking,this thesis provided the design of real-time scheduling model, and gave the examples of supporting "unloading with loading" and "heavy come heavy go" operation mode in real-time scheduling system. It can provide a comprehensive reference model for future development of container terminal.
集装箱码头资源优化与调度研究涉及管理学、运筹学、信息科学、港口工程等许多相关领域的研究,本文研究的集装箱码头实时调度系统也是多种理论和技术的集成应用体。通过本文研究将对集装箱码头的调度体系和理论、组合优化理论、对多Agent和移动Agent应用框架和机制在集装箱码头生产作业中的应用、完善和推广起到积极的作用。本文采用基于AUML的面向Agent分析方法设计了集装箱码头实时调度系统的功能和交互模型。应用这种模型对进一步提高码头生产资源的利用率,加强生产作业环节的协作性,提高码头作业效率和吞吐能力,对提高码头应对突发事件的响应能力,保障码头作业连续性、稳定性及提高客户满意度等均有现实意义。
本文完成的主要研究工作包括：
(1)研究了基于Agent的集装箱码头实时调度框架模型。
本文基于AUML的AOA方法,逐步设计了集装箱码头实时调度系统的角色行为模型、结构框架模型和交互模型,从宏观的角度分析了实时调度系统的功能,各功能间的关系以及协同工作的交互方式,给出了系统的框架模型。
(2)进行了面向实时调度的智能计划Agent设计。
主要研究了面向实时调度的、支持动态调整的、智能的生产计划编制方法。结合Agent的功能结构,较为详细地设计了泊位岸桥计划Agent、单船计划Agent、资源配置计划Agent的功能模型,提出了相关的优化算法。论文中还总结了各Agent如何协同工作实现针对现场突发事件的实时调度以及Agent环境数据获取的优化方法。
(3)设计了基于移动Agent技术的岸桥-集卡-场桥协同作业的实时调度模型。
本文通过引入移动Agent技术,重点研究其移动机制、移动策略、通信机制等关键问题,充分利用移动Agent能够节约网络带宽、克服网络延迟、支持异步自主执行、具有动态适应性、增强应用的鲁棒性和容错能力等技术优势,设计出了现场岸桥-集卡-场桥协同作业模型,提高了实时调度系统及时响应能力和鲁棒性。
总体来讲,本文通过针对集装箱码头实时调度系统的模型设计,并用实例论述了模型对“边装边卸”、“重来重去”等有实时调度特色的作业模式的支持,能够为将来全面设计开发集装箱码头实时调度系统提供了一套较为全面的参考模型。
As wireless communication, mobile terminal, distributed data processing information technology in container terminal is becoming more and more popular, a new kind of Container Terminal Scheduling model of Real-time is put forward. Compared with the traditional scheduling model it is more useful to improve efficiency of resource utilization and terminal operation. The researches on Container terminal resources optimization and dispatching management involve management, operations research, information science, port engineering and many related fields. So Container terminal real-time scheduling system is the integration of theory and application of technology. The study in this thesis can play an active role in the application, perfection, popularization of the theory of container terminal operation system, the theory of combinatorial optimization, application framework of Mulit-Agent and Mobile-Agent. Based on Agent Oriented Analysis using AUML, the function and interactive model of container terminal real-time scheduling system were designed in this thesis. Applying this model to further improve the utilization of productive resources, to strengthen cooperation between operations, to improve the working efficiency and throughput capacity of wharf, to guarantee the stability and continuity of terminal operations, to improve customer satisfaction has practical significance.
Mainly studies completed in the paper include:
(1) Researched on real-time scheduling framework model based on Agent
Based on the method of AUML AOA, the Role-Active model, the Structural Framework Model, and the interactive model were designed. These models analyzed the functions, the relation between functions and the interactive mode in Real-time scheduling system from the macroscopic Angle, and all these models macroscopic Angle made up system framework model.
(2) Designed Real-time scheduling oriented intelligent Plan Agents
Real-time oriented, supporting dynamic adjustment, intelligent operation planning methods were studied. In this thesis Berth-crane plan Agent model, Ship plan Agent model, Machine plan Agent model were designed in detail. And relevant optimization algorithms were put forward. The thesis also summarized how Agents collaborative work to realize real-time scheduling for emergency, and optimization methods of acquiring Agent environmental data.
(3) Designed Real-time operation model by cooperation with shore crane, truck based on Mobile-Agent technology
Mobile-Agent technology has many advantages such as save network bandwidth, overcome the network latency, support asynchronous independent execution, with dynamic adaptability, enhance application robustness and tolerance, etc. These advantages are very important for real-time scheduling in wireless-network environment. The thesis provided a real-time operation model based on mobile-agent and give the detail explanation of architecture and working mechanism, discuss the key technology in design and implementation. This model can reduce influence of the quality of wireless network communication on system, improve the system response ability and offer a new method to implement real-time dispatcher in container terminal.
Generally speaking,this thesis provided the design of real-time scheduling model, and gave the examples of supporting "unloading with loading" and "heavy come heavy go" operation mode in real-time scheduling system. It can provide a comprehensive reference model for future development of container terminal.
引文
[1]宗蓓华,真虹,港口装卸工艺学[M],人民交通出版社,2003
[2]孙凤山,港口发展集装箱物流的优势和途径现代物流[J],港口经济,2007,2：33-5
[3]Davidson, N. A global Capacity assessment and needs analysis[C], Proeeedings of the 39th Terminal Operating Conferenee, Antwerp, Belgium,2005.
[4]VicentJ.Botti, Multi-Agent System Technology in a port Container Terminal Automation[J], ERCIM News No.56,2004:37-9
[5]Sha, Mei. A simulation model for intra-terminal transport of container terminal operations system. Proceedings of 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, IEEE/SOLI 2008:2810-2814
[6]Yan, Nannan. A multi-agent system for container terminal management [J]. Proceedings of the World Congress on Intelligent Control and Automation (WCICA2008), 2008:6241-6246
[7]Shen, Yi. Design and implementation of the container terminal operating system based on service-oriented architecture (SOA)[J]. Proceedings of the 2008 International Conference on Cyberworlds,2008:794-799
[8]W. C. Ng, K. L. Mak, Y. X. Zhang. Scheduling trucks in container terminals using a genetic algorithln[J]. Engineering Optimization,2007,39(1):33-47
[9]Patrick J. M. Meersmans, Albert P.M.Wagelmans. Dynamic scheduling Of handling equipment at automate container terminals[J], Erim report series research in management,2002.1:69-89.
[10]Zhang, H.-L. Simulation studies of heuristic approaches for dynamic scheduling of container terminal operations [J]. International Journal of Modelling and Simulation,2008,28 (4):410-422.
[11]Nathan Nhan Huynh. Methodologies for Reducing Truck TurnTime at Marine Container Termials [D]. The University of Texas at Austin 2005
[12]Kluwer, Boston. Vehicle dispatching at seaport container terminals using evolutionary algorithms[J]. Optimization and Simulation,2000,75:91-114
[13]钱永兴.集装箱码头集卡调度系统[J].水运工程,2005,05：62—66
[14]杨静蕾,丁以中.集装箱码头设备配置的模拟研究[J].系统仿真学报,2003,15(8).
[15]魏众,集装箱码头物流作业系统集成优化调度研究[D],北京交通大学,2007.3
[16]周鹏飞,面向不确定环境的集装箱码头优化调度研究[D],大连理工大学,2005.10
[17]韩笑乐等,集装箱码头岸吊作业调度建模及调度策略研究[J],工业工程与管理,2009.10(14)520-26
[18]吕显强,张宏伟.集装箱码头分派车辆的整数规划模型[J].大连水产学院学报,2004,19(6).
[19]于蒙.基于多Agent的集装箱码头生产调度系统的研究[D].武汉理工大学,2007
[20]王慧来.天津港集装箱码头作业管理的业务重组与技术创新[J].中国新技术新产品,2009(20)：81
[21]冯梅.定位技术在集装箱码头的综合利用[J].中国港口,2009(9)：59-60.
[22]Liu, Hai-Ning. Visual modeling of virtual container terminal based on GPS/GIS[J]. Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2009,43(6):866-870
[23]Sha, Mei. A simulation model for intra-terminal transport of container terminal operations system [J]. Proceedings of 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, IEEE/SOLI 2008:2810-2814.
[24]Imai A, Nishimura E, Papadimitriou S. The dynamic berth allocation problem for a container Port [J]. Transportation Research Part B,2001,35:401-417.
[25]NishimuraE, ImaiA, Papadimitriou S. Berth allocation planning in the public berth system by genetic algorithms [J]. European Journal of Operational Researeh,2001, 131:282-292.
[26]ImaiA, NishimuraE, Papadimitriou S. Berth allocation With service Priority[J]. Transportation Researeh Part B,2003,37:437-57.
[27]Lai K K, Shih K. A Study of Container Berth Allocation[J]. Journal of Advanced Transportation,1992,26(1):45-60.
[28]Lim A. The berth seheduling Problem[J]. Operations Researeh Letters 1998,22:105-110
[29]Kim K Y, Kim K H. An optimal routing algorithm for a transfer crane in Port Container terminals[J]. Transportation Scienee,1999c,33(1):17-33.
[30]Li C L, Cai X, Lee C Y. Scheduling with multiple job-on-one-processor pattern [J]. IIE Transactions 1998,30:433-445.
[31]Guan Y P, et. A multi Processor task scheduling model for berth allocation:heuristic and worst-case analysis[J]. Operations Researeh Letters,2002,30:343-350.
[32]Daganzo C F. The crane scheduling Problem[J]. Transportation Researeh B,1989, 23 (3):159-175.
[33]Brown G G, Cormiean K J, Lawphongpanich S, Widdis D B. Optimizing submarine berthing with a Persistenve incentive[J]. Naval Researeh Logisties,1997,44:301-318.
[34]Kap Hwan Kim, Young-Man Park. A crane seheduling method for Port container terminals[J]. European Journal of Operational Research,2004,156:752-768
[35]Brown G G, Lawphong Panich S, Thurman KP. Optimizing ship berthing [J]. Naval Research Logistics,1994,41:1-15.
[36]Peterkofsky R L, Daganzo C F. A branch and bound solution method for the crane scheduling Problem[J]. TransPortation Research B,1990,24(3):159-172.
[37]W. C. Ng, Crane scheduling in container yards with inter-crane interference[J].European Journal of Operational Research,2005,164:64-78
[38]KozanE, PrestonP. Genetic algorithm to schedule container transfers at multimodal terminals [J]. International Transactions of Operational Researeh,1999,6:311-329
[39]Bthrokh Khoshenevis.3D Virtual and Physical Simulation of Automated Container Terminal and Analysis of Impact on In Land Transportation[D]. Universityof Southern California,2000.
[40]KaP Hwan Kima, Ki Young Kim. Routing straddle carriers for the loading operation of containers using a beam search algorithm[J]. Computers and Industrial Engineering,1999,36:109-136.
[41]屈援,王雪莲.有卸货顺序约束的集装箱装载问题及算法研究[J],计算机工程与设计2008,29(7)：1789-1791
[42]J. f Shen, et. Nested Genetic Algorithm for Optimal Container Pickup Operation Scheduling on Container Yards[J]. ICNC,06 and FSKD,2006,06:666-675
[43]Avriel M, penn M, Shpirer N, and Witteboon S. Stowage planning for Container Ship to Reduce the Number of shifts[J]. Annals of Operation Researeh,1998,76:55-71.
[44]缪立新.集装箱装船顺序优化模型及算法研究[R].清华大学,2004
[45]彭传圣.港口码头系统计算机模拟技术应用的现状与发展[J].水运科学研究所学报,1999,6：1-10.
[46]李冠声等.上海港集装箱码头吞吐能力与设备配置优化[J].集装箱运输.2002(8)：25-26
[47]邢文训,谢金星,现代优化计算方法[M],清华大学出版社,2005.9
[48]王凌.车间调度及其遗传算法[M]一比京：清华大学出版社,2003
[49]胡运权.运筹学教程[M],北京：清华大学出版社
[50]杨剑峰.蚁群算法及其应用研究[D],浙江大学,2007
[51]武妍,周欣.一种适用于求解TSP问题的改进的禁忌算法[J],计算机工程与应用,2008,44(1)：57-59
[52]陈泯融.基于极值动力学的优化方法及其应用研究[D],上海交通大学,2008
[53]刘志雄.调度问题中的粒子群优化方法及其应用研究[D].武汉理工大学,2005
[54]衣杨,汪定伟.并行多机成组工作总流水时间调度问题[J].计算机集成制造系统,2001,7(7)：7-11
[55]郑向位.求解优化问题的微粒群算法及其应用研究[D],山东师范大学,2008
[56]HE Yi. A parallel tabu search approach based on genetic crossover operation[C], Proc of 19th IEEE Int'1 Conf on Advanced Information Networking and Applications. Taipe:IEEE Computer Society Press,2005:1550-1553.
[57]李霄峰,等.混合流水车间调度的变邻域禁忌搜索算法[J],计算机工程,2008.34(21)：10-12
[58]李霄峰,邵惠鹤.求解HFS调度问题的简化禁忌搜索方案[J].上海交通大学学报,2003,37(4)：315-320
[59]Loukil T, Teghem J, Tuyttens D. Solving multi-objective production scheduling problems using meta-heuristics[J]. European Journal of Operational Research, 2005,161:42-61.
[60]赵怀慈,等.基于Agent的复杂系统智能仿真建模方法的研究[J].系统仿真学报,2003,15(7)：910-913
[61]赵欣培.一种基于Agent的软件过程建模方法研究[D].中国科学院研究生院,2004
[62]顾绍元,等.一种基于Agent的需求分析与建模方法[J],计算机工程与应用,2001,(5)：38-40
[63]钟凌燕,等.一种基于UML的本体论建模方法[J].计算机工程,2003,29(2)：38-39
[64]刘炜,等一种基于扩展I*框架和UML的面向Agent需求建模方法[J].小型微型计算机系统,2005,26(5)：855-860
[65]唐跃平,等.一种面向Agent建模方法的研究[J].指挥技术学院学报,2000,11(3)：53-56
[66]毛新军,等.Modeling dynamic Agent with Role transition Diagram[J].计算机科学,2006,33(8)：225-227
[67]赵骥,等.制造系统虚拟环境的多Agent建模方法[J].中国机械工程,2002， 13(8)：660-662
[68]蒋云良,等.智能Agent与多Agent系统的研究[J].计算机应用研究,2003,(3)：31-34
[69]柳娟,等.面向Agent的软件开发方法[J].北京工商大学学报(自然科学版),2006,24(1)：46-48
[70]李航,等.UML系统动态行为描述方案[J].计算机工程与设计,2002,23(8)：28-30
[71]徐明,等.基于XML的多Agent系统的研究与实现[J].计算机科学,2006,33(2)：205-208
[72]Odell J, ParunakH, Bauer, B. Representing Agent Interactions Protoeols in UML [R].AAAI Agents 2000 conference,2000
[73]刘大有,等.Agent研究现状与发展趋势[J].软件学报,2000,11(3)：315-321
[74]Wooldridge M, Jennings N R, Kinny David. The gaia methodology for agent-oriented Analysis and design[J]. Autonomous Agents and Multi-Agent Systems,2000, 3(3):285-312
[75]陈磊,等.基于AUML与GPN的Agent交互协议建模[J].计算机工程与科学,2006,28(4)：107-110
[76]边小凡,赵芳芳.基于移动Agent实现构件与Web服务的企业应用集成[J],计算机工程与设计,2009,29(6)：4363-4366
[77]李祥.IBM移动Agent平台[EB/OL]. http://210.40.7.188/Eyan/02/05. htm.
[78]MadriaS K, Mohania M. Mobile Data and Transaction Mangement[J]. Information Science,2000, (141):279-309
[79]Robert S G. A Flexible and Secure Mobile Agent System[D]. Dartmouth College,2005, 22(2)
[80]闵玉堂,容太平.移动Agent系统结构及其关键技术[J].武汉理工大学报,2003,25(1)：22-25
[81]何炎祥,陈莘萌.Agent和多Agent系统的设计与应用[M].武汉大学出版社,2001
[82]刘婷.基于移动Agent的协商机制的研究与应用[D].大连海事大学,2009
[83]樊玉,杰李俊.基于移动Agent的网络化远程监控系统设计[J].数采与监测,2008,24(5-1)：93-95
[84]魏晓斌、周盛宗等.Agent通信机制探讨[J].计算机工程与应用,2002,5：66-70.
[85]郭健.基于多Agent的智能管理信息系统研究[D],天津大学管理学院,2004
[86]王欣,移动Agent在移动数据库中应用技术研究[D],哈尔滨理工大学,2009
[87]董红斌、李滨丽、李洪峰,基于Mobile Agent的信息搜索技术[J],哈尔滨师范大学自然科学学报,2002,18(2)：52-57
[88]陈东娅.基于移动Agent的电子商务通信研究[J].电子技术,2009：79-80
[89]洪流.基于MAS的协调知识与协调策略研究[D],华中科技大学,2007
[90]张欧亚,佟明安.基于AUML的面向Agent分析方法及其应用[J],计算机工程与应用,2007,43(2)：244-248
[91]郑广海,曲英伟.基于Agent的软件系统开发方法[J].微机发展,2003(6)：117-120
[92]Bauer B, Muller J P, Odell J. Agent UML:a formalism for specifying multiagent software systems[C]//The First International Workshop on Agent-Oriented Software Engineering(AOSE'2000). Berlin:Springer-Verlag,2000.
[93]Arlow J, Neustadt I. UML和统一过程(实用面向对象的分析和设计)[M].北京：机械工业出版社,2003-02.
[94]李俊青,等.基于AUML的面向Agent的ERP系统设计[J],计算机工程与设计,2007,28(20)：5012-5017
[95]翁文勇,王泽兵,冯雁.UML技术在面向Agent系统分析中的应用研究[J].计算机工程与设计,2004,25(7)：1140-1142.
[96]吴文斌.一种面向Agent的分析与设计方法[J].小型微型计算机系统,2003,24(3)：456-459.
[97]王家伟,等.一种基于移动Agent的分布式信息检索优化模型[J].计算机科学,2008.35(7)：292-294
[98]赵龙文,侯义斌.智能软件：由面向对象到面向Agent[J].计算机工程与应用,2001(5)：41-43.
[99]张云勇,刘锦德.移动Agent技术[M].北京：清华大学出版社,2003.
[100]冯 锋.基于移动Agent的Web服务系统模型研究与构建[J],计算机技术与发展,2008.18(2)：247-250
[101]黄冬梅,等.基于移动Agent的W ebGIS体系结构[J],计算机应用与软件,2008.25(3)：56-58
[102]王栩.Agent系统通讯理论及组织结构的研究[D].中国科学院软科二研究所,2000
[103]游晓明,等.基于扩展UML的Agent建模语言的设计与研究[J],小型微型计算机系统,2006,27(3)：534-537
[104]Ruiz R. Maroto C. A Genetic Algorithm for Hybrid Flowshops with Sequence Dependent Setup Times and Machine Eligibility [J], European Journal of operational Research, 2006,169(3):781-800.
[105]邸向珍,赵守香.基于移动Agent的电子商务模型的研究与分析.北京工商大学学报(自然科学版),2009,27(5)：54-56
[106]肖丹丹,等.改进的蚁群算法在移动Agent迁移中的应用研究[J],成都大学学报,2008,27(1)：41-44
[107]骆正虎.移动Agent系统若干关键技术问题研究[D].合肥：合肥工业大学,2002.
[108]胡海洋,胡华,凌云.MAwA：基于移动Agent的一种高效可靠无线Web访问机制[J],计算机研究与发展,2008,45(4)：636-645
[109]E Pitoura, G Samaras. Data Management for Mobile Computing[M], Amsterdam, Netherlands:Kluwer Academic Publishers,1998
[110]J Jing, A S Helal. Client-server computing in mobile environments [J]. ACM Computing Survey,1999,31 (2):117-157
[111]徐沛娟.基于移动agent的分布式入侵检测系统研究[J],计算机应用研究,2009,26(10)：3898-3900
[112]马良,项培军.蚁群算法在组合优化中的应用[J].管理科学学报,2001,4(2)：32-37
[113]王万良.生产过程的智能调度方法及其应用[D].浙江：同济大学,2001
[114]李工农.基于非线性规划的组合优化算法[D].北京：中国科学院数学与系统科学研究院,2003
[115]Kendall, E. A. Agent roles and role models [EB/OL]. URL:http://www. labs. bt. com/Projects/ibsr/Papers/Patterns/iaipm. ps. gz,2002
[116]薛霄.面向Agent的软件设计开发方法[M],北京：电子工业出版社,2009
[117]高阳,江资斌.基于扩展UML的虚拟企业多Agent协作建模研究[J].制造技术与机床,2006,(2)：108-111
[118]Miao Kang, et. Modelling Mobile Agent Applications in UML 2.0 Activity Diagrams[C/OL], (04-04-21), http://www. auml. org/auml/supplements/UML2-AD. pdf
[119]James Odell, Marian Nodine, Renato Levy. FIPA Modeling:Agent Class Superstructure Metamode [C/OL], FIPA TC Modeling, (04-01-21), http://www. auml. org/auml/documents/CD2-03-10-31. doc
[120]毛国君,等.数据挖掘原理与算法[M],北京：清华大学出版社,2005
[121]Rehemujiang, et. Cooperative Multi-AGENT System in Diagnosing the WellDrilling Malfunction and Aceident Solving[J], Proceedings of the Seventh International Conference on CSCW in Design, September,2002, Rio de Janeiro, Brazil,:231-235.
[121]王汝传,徐小龙、黄海平,智能Agent及其在信息网络中的应用[M],北京邮电大学出版社,2006
[122]王曼君.集成化的集装箱码头管理信息系统[J]港口装卸,2001,4：25-27
[123]计三有,刘德鹏.集装箱码头交通运输组织建模及仿真技术研究[J].水运工程,2006,5：22-25
[124]马良,朱刚,宁爱兵,蚁群优化算法[M],科学出版社,2008.2
[125]黄红选,韩继业,数学规划[M],清华大学出版社,2006,3
[126]Botter R C. Stowage container planning:a model for getting an optimal solution[J]. IFIP Transaetion B:Computer Applications in Technology,1992, 5:217-229.
[127]Crainie T G, Gendreau M, Dejax P, Dynamic and stochastic models for the allocation of empty containers[J]. Operations Research,1993,41:102-126.
[128]Shen W S, Khoong C M. A DSS for empty container distribution planning [J]. Decision Support Systems,1995,5:75-82.
[129]Lai Y J, Hwang C L. Fuzzy Mathematical Programming[M]. Berlin:Springer Verleg, 1992.
[130]廖强,周凯,张伯鹏,基于现场总线的多Agent作业车间动态调度问题的研究[J].机械科学与技术.2000,21(4),757-760
[131]Kap Hwan Kim, Seung Hwan Won, Jae Kook Lim. An arehitectural design of Control software for automated container terminals [J], Computers& Industrial Engineering, 2004,46:741-754
[132]杨志新.集装箱码头业务管理信息系统的实践[J].交通与计算机,2005,23(2)：122-126
[133]DEGANO, et. "Multi-Agent Coordination and Collaboration for Controland Optimization Strategies in an Intermodal Container Terminal[C], IEEE InternationalEngineering Management Conference (IEMC-2002), Cambridge, UK, IEEE.
[134]Gambardella, et. Simulation and Planning of an intermodal container terminal[C], Simulation71(2):107 -116.
[135]REBOLLO, et.A Multi-Agent System for the Automation of a Port Container Terminal[C], Autonomous Agents 2000 workshop on Agents in Industry. Bareelona, Spain.
[136]Thurston, et, Distributed Agent Architecture Automation[J],26th International Computer Software and Conferenee,2002, Oxford, UK,:81-90.
[137]范中洲.大连智能虚拟港口[J].海事大学学报.2005,31(1)
[138]A. A. Shabayek, W. W. Yeung. A simulation model for the Kwai Chung container terminals In HongKong[J]. EuroPean Journal of Operational Research 2002:1-11
[139]樊晓平,罗熊,易晟,等.复杂环境下基于蚁群优化算法的机器人路径规划[J].控制与决策,2004,19(2)：166-170.
[l40]Poli Riccardo, Kennedy James, Blackwell Tim. Particle swarm optimization--an overview. Swarm Intell,2007(1):33-57.
[141]Ozcan E and Mohan CK. Analysis of a simple particle swarm optimization system. Intelligent Engineering Systems Through Artificial Neural Networks,1998,8:253-258.
[142]Ozcan E, Mohan C. Particle swarm optimization:surf ing the waves. In Proceedings of the IEEE congress on evolutionary computation(CEC 99),1999, pp.1939-1944.
[143]胡旺,李志蜀.一种更简化而高效的粒子群优化算法.软件学报,2007,18(4)：861-868.
[144]寇晓丽,刘三阳.一种随机微粒群混合算法求解约束优化问题.系统仿真学报,2007,19(10)：1248-2150.
[145]陈国初,俞金寿.单纯形微粒群优化算法及其应用[J].系统仿真学报,2006,18(4)862-865.
[146]Vis, et. Determination of the number of automated guided vehicles required at a semi-automated container terminal[J].Journal of the Operational Researeh Society,2001,52:409-417.
[147]杨杨,提高集装箱码头堆场使用率的问题研究[J],中国新技术新产品,2009(20)：81
[148]真虹.集装箱运输学[M].大连：大连海事大学出版1999
[149]Chen C Y, Hsieh T W. A Time-Space Network Model for the Berth Allocation Problem[C].19th IFIP TC6 Conference on System Modeling and Optimization, Cambridge, UK,1999,7.
[150]Hurink J, Juriseh B, Thole M. Tabu Search for Job-shop schduling Problem with Multipurpose Maehines[J]. OR Speektrum,1994,15(5):205-215
[151]熊一龙.基于移动Agent的无线webservice的技术研究[D].武汉理工大学,2009
[152]N. Pissinou, C. Dunu. A New Framework for Handling Mobile Clients in a Client-Server Database System[C]. The University of Southwestern Louisiana, Computer Communications,2000.5
[153]单国华.移动Agent数据保护的研究[D],合肥工业大学,2009
[154]魏登文.面向电子商务税收征管的移动Agent信任模型及其应用研究[D],华中科技大学,2009
[155]Evers J J M, Koppers S A J. Automated guided vehicle traffic control at a container terminal[J]. Transportation Researeh A,1996,30(1):21-34.
[156]Lai K K, Leung M. A Study of Gate Lane Allocation in Container Terminal [J]. Journal of Advanced Tansportation,1996,30(3):26-38
[157]Jiao, Ai-Ying. An empirical research of bohai rim container terminal based on PDEA model[J].2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008:1137-1141
[158]Legato P, Mazza R M. Berth Planning and resources optimization at a container terminal via discrete event simulation[J]. European Joumal of Operational Researeh,2001,133(3):537-547.
[159]Li. Modeling and simulation of container terminal logistics system[J].2009 2nd International Workshop on Knowledge Discovery and Data Mining, WKKD 2009:729-732
[160]Zhao, Hui. Research on container terminal scheduling system based on multi-agent[J]. Proceedings-2009 IITA International Conference on Control, Automation and Systems Engineering, CASE 2009:399-402
[161]Yan, Nannan. A multi-agent-based production dispatching information integration system for an automated container terminal[J]. Proceedings of the 2008 IEEE International Conference on Information and Automation, ICIA 2008:1117-1122
[162]Nguyen, Vu Duc. A dispatching method for automated lifting vehicles in automated port container terminals[J]. Computers and Industrial Engineering,2009,56(3): 1002-1020
[2]孙凤山,港口发展集装箱物流的优势和途径现代物流[J],港口经济,2007,2：33-5
[3]Davidson, N. A global Capacity assessment and needs analysis[C], Proeeedings of the 39th Terminal Operating Conferenee, Antwerp, Belgium,2005.
[4]VicentJ.Botti, Multi-Agent System Technology in a port Container Terminal Automation[J], ERCIM News No.56,2004:37-9
[5]Sha, Mei. A simulation model for intra-terminal transport of container terminal operations system. Proceedings of 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, IEEE/SOLI 2008:2810-2814
[6]Yan, Nannan. A multi-agent system for container terminal management [J]. Proceedings of the World Congress on Intelligent Control and Automation (WCICA2008), 2008:6241-6246
[7]Shen, Yi. Design and implementation of the container terminal operating system based on service-oriented architecture (SOA)[J]. Proceedings of the 2008 International Conference on Cyberworlds,2008:794-799
[8]W. C. Ng, K. L. Mak, Y. X. Zhang. Scheduling trucks in container terminals using a genetic algorithln[J]. Engineering Optimization,2007,39(1):33-47
[9]Patrick J. M. Meersmans, Albert P.M.Wagelmans. Dynamic scheduling Of handling equipment at automate container terminals[J], Erim report series research in management,2002.1:69-89.
[10]Zhang, H.-L. Simulation studies of heuristic approaches for dynamic scheduling of container terminal operations [J]. International Journal of Modelling and Simulation,2008,28 (4):410-422.
[11]Nathan Nhan Huynh. Methodologies for Reducing Truck TurnTime at Marine Container Termials [D]. The University of Texas at Austin 2005
[12]Kluwer, Boston. Vehicle dispatching at seaport container terminals using evolutionary algorithms[J]. Optimization and Simulation,2000,75:91-114
[13]钱永兴.集装箱码头集卡调度系统[J].水运工程,2005,05：62—66
[14]杨静蕾,丁以中.集装箱码头设备配置的模拟研究[J].系统仿真学报,2003,15(8).
[15]魏众,集装箱码头物流作业系统集成优化调度研究[D],北京交通大学,2007.3
[16]周鹏飞,面向不确定环境的集装箱码头优化调度研究[D],大连理工大学,2005.10
[17]韩笑乐等,集装箱码头岸吊作业调度建模及调度策略研究[J],工业工程与管理,2009.10(14)520-26
[18]吕显强,张宏伟.集装箱码头分派车辆的整数规划模型[J].大连水产学院学报,2004,19(6).
[19]于蒙.基于多Agent的集装箱码头生产调度系统的研究[D].武汉理工大学,2007
[20]王慧来.天津港集装箱码头作业管理的业务重组与技术创新[J].中国新技术新产品,2009(20)：81
[21]冯梅.定位技术在集装箱码头的综合利用[J].中国港口,2009(9)：59-60.
[22]Liu, Hai-Ning. Visual modeling of virtual container terminal based on GPS/GIS[J]. Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2009,43(6):866-870
[23]Sha, Mei. A simulation model for intra-terminal transport of container terminal operations system [J]. Proceedings of 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, IEEE/SOLI 2008:2810-2814.
[24]Imai A, Nishimura E, Papadimitriou S. The dynamic berth allocation problem for a container Port [J]. Transportation Research Part B,2001,35:401-417.
[25]NishimuraE, ImaiA, Papadimitriou S. Berth allocation planning in the public berth system by genetic algorithms [J]. European Journal of Operational Researeh,2001, 131:282-292.
[26]ImaiA, NishimuraE, Papadimitriou S. Berth allocation With service Priority[J]. Transportation Researeh Part B,2003,37:437-57.
[27]Lai K K, Shih K. A Study of Container Berth Allocation[J]. Journal of Advanced Transportation,1992,26(1):45-60.
[28]Lim A. The berth seheduling Problem[J]. Operations Researeh Letters 1998,22:105-110
[29]Kim K Y, Kim K H. An optimal routing algorithm for a transfer crane in Port Container terminals[J]. Transportation Scienee,1999c,33(1):17-33.
[30]Li C L, Cai X, Lee C Y. Scheduling with multiple job-on-one-processor pattern [J]. IIE Transactions 1998,30:433-445.
[31]Guan Y P, et. A multi Processor task scheduling model for berth allocation:heuristic and worst-case analysis[J]. Operations Researeh Letters,2002,30:343-350.
[32]Daganzo C F. The crane scheduling Problem[J]. Transportation Researeh B,1989, 23 (3):159-175.
[33]Brown G G, Cormiean K J, Lawphongpanich S, Widdis D B. Optimizing submarine berthing with a Persistenve incentive[J]. Naval Researeh Logisties,1997,44:301-318.
[34]Kap Hwan Kim, Young-Man Park. A crane seheduling method for Port container terminals[J]. European Journal of Operational Research,2004,156:752-768
[35]Brown G G, Lawphong Panich S, Thurman KP. Optimizing ship berthing [J]. Naval Research Logistics,1994,41:1-15.
[36]Peterkofsky R L, Daganzo C F. A branch and bound solution method for the crane scheduling Problem[J]. TransPortation Research B,1990,24(3):159-172.
[37]W. C. Ng, Crane scheduling in container yards with inter-crane interference[J].European Journal of Operational Research,2005,164:64-78
[38]KozanE, PrestonP. Genetic algorithm to schedule container transfers at multimodal terminals [J]. International Transactions of Operational Researeh,1999,6:311-329
[39]Bthrokh Khoshenevis.3D Virtual and Physical Simulation of Automated Container Terminal and Analysis of Impact on In Land Transportation[D]. Universityof Southern California,2000.
[40]KaP Hwan Kima, Ki Young Kim. Routing straddle carriers for the loading operation of containers using a beam search algorithm[J]. Computers and Industrial Engineering,1999,36:109-136.
[41]屈援,王雪莲.有卸货顺序约束的集装箱装载问题及算法研究[J],计算机工程与设计2008,29(7)：1789-1791
[42]J. f Shen, et. Nested Genetic Algorithm for Optimal Container Pickup Operation Scheduling on Container Yards[J]. ICNC,06 and FSKD,2006,06:666-675
[43]Avriel M, penn M, Shpirer N, and Witteboon S. Stowage planning for Container Ship to Reduce the Number of shifts[J]. Annals of Operation Researeh,1998,76:55-71.
[44]缪立新.集装箱装船顺序优化模型及算法研究[R].清华大学,2004
[45]彭传圣.港口码头系统计算机模拟技术应用的现状与发展[J].水运科学研究所学报,1999,6：1-10.
[46]李冠声等.上海港集装箱码头吞吐能力与设备配置优化[J].集装箱运输.2002(8)：25-26
[47]邢文训,谢金星,现代优化计算方法[M],清华大学出版社,2005.9
[48]王凌.车间调度及其遗传算法[M]一比京：清华大学出版社,2003
[49]胡运权.运筹学教程[M],北京：清华大学出版社
[50]杨剑峰.蚁群算法及其应用研究[D],浙江大学,2007
[51]武妍,周欣.一种适用于求解TSP问题的改进的禁忌算法[J],计算机工程与应用,2008,44(1)：57-59
[52]陈泯融.基于极值动力学的优化方法及其应用研究[D],上海交通大学,2008
[53]刘志雄.调度问题中的粒子群优化方法及其应用研究[D].武汉理工大学,2005
[54]衣杨,汪定伟.并行多机成组工作总流水时间调度问题[J].计算机集成制造系统,2001,7(7)：7-11
[55]郑向位.求解优化问题的微粒群算法及其应用研究[D],山东师范大学,2008
[56]HE Yi. A parallel tabu search approach based on genetic crossover operation[C], Proc of 19th IEEE Int'1 Conf on Advanced Information Networking and Applications. Taipe:IEEE Computer Society Press,2005:1550-1553.
[57]李霄峰,等.混合流水车间调度的变邻域禁忌搜索算法[J],计算机工程,2008.34(21)：10-12
[58]李霄峰,邵惠鹤.求解HFS调度问题的简化禁忌搜索方案[J].上海交通大学学报,2003,37(4)：315-320
[59]Loukil T, Teghem J, Tuyttens D. Solving multi-objective production scheduling problems using meta-heuristics[J]. European Journal of Operational Research, 2005,161:42-61.
[60]赵怀慈,等.基于Agent的复杂系统智能仿真建模方法的研究[J].系统仿真学报,2003,15(7)：910-913
[61]赵欣培.一种基于Agent的软件过程建模方法研究[D].中国科学院研究生院,2004
[62]顾绍元,等.一种基于Agent的需求分析与建模方法[J],计算机工程与应用,2001,(5)：38-40
[63]钟凌燕,等.一种基于UML的本体论建模方法[J].计算机工程,2003,29(2)：38-39
[64]刘炜,等一种基于扩展I*框架和UML的面向Agent需求建模方法[J].小型微型计算机系统,2005,26(5)：855-860
[65]唐跃平,等.一种面向Agent建模方法的研究[J].指挥技术学院学报,2000,11(3)：53-56
[66]毛新军,等.Modeling dynamic Agent with Role transition Diagram[J].计算机科学,2006,33(8)：225-227
[67]赵骥,等.制造系统虚拟环境的多Agent建模方法[J].中国机械工程,2002， 13(8)：660-662
[68]蒋云良,等.智能Agent与多Agent系统的研究[J].计算机应用研究,2003,(3)：31-34
[69]柳娟,等.面向Agent的软件开发方法[J].北京工商大学学报(自然科学版),2006,24(1)：46-48
[70]李航,等.UML系统动态行为描述方案[J].计算机工程与设计,2002,23(8)：28-30
[71]徐明,等.基于XML的多Agent系统的研究与实现[J].计算机科学,2006,33(2)：205-208
[72]Odell J, ParunakH, Bauer, B. Representing Agent Interactions Protoeols in UML [R].AAAI Agents 2000 conference,2000
[73]刘大有,等.Agent研究现状与发展趋势[J].软件学报,2000,11(3)：315-321
[74]Wooldridge M, Jennings N R, Kinny David. The gaia methodology for agent-oriented Analysis and design[J]. Autonomous Agents and Multi-Agent Systems,2000, 3(3):285-312
[75]陈磊,等.基于AUML与GPN的Agent交互协议建模[J].计算机工程与科学,2006,28(4)：107-110
[76]边小凡,赵芳芳.基于移动Agent实现构件与Web服务的企业应用集成[J],计算机工程与设计,2009,29(6)：4363-4366
[77]李祥.IBM移动Agent平台[EB/OL]. http://210.40.7.188/Eyan/02/05. htm.
[78]MadriaS K, Mohania M. Mobile Data and Transaction Mangement[J]. Information Science,2000, (141):279-309
[79]Robert S G. A Flexible and Secure Mobile Agent System[D]. Dartmouth College,2005, 22(2)
[80]闵玉堂,容太平.移动Agent系统结构及其关键技术[J].武汉理工大学报,2003,25(1)：22-25
[81]何炎祥,陈莘萌.Agent和多Agent系统的设计与应用[M].武汉大学出版社,2001
[82]刘婷.基于移动Agent的协商机制的研究与应用[D].大连海事大学,2009
[83]樊玉,杰李俊.基于移动Agent的网络化远程监控系统设计[J].数采与监测,2008,24(5-1)：93-95
[84]魏晓斌、周盛宗等.Agent通信机制探讨[J].计算机工程与应用,2002,5：66-70.
[85]郭健.基于多Agent的智能管理信息系统研究[D],天津大学管理学院,2004
[86]王欣,移动Agent在移动数据库中应用技术研究[D],哈尔滨理工大学,2009
[87]董红斌、李滨丽、李洪峰,基于Mobile Agent的信息搜索技术[J],哈尔滨师范大学自然科学学报,2002,18(2)：52-57
[88]陈东娅.基于移动Agent的电子商务通信研究[J].电子技术,2009：79-80
[89]洪流.基于MAS的协调知识与协调策略研究[D],华中科技大学,2007
[90]张欧亚,佟明安.基于AUML的面向Agent分析方法及其应用[J],计算机工程与应用,2007,43(2)：244-248
[91]郑广海,曲英伟.基于Agent的软件系统开发方法[J].微机发展,2003(6)：117-120
[92]Bauer B, Muller J P, Odell J. Agent UML:a formalism for specifying multiagent software systems[C]//The First International Workshop on Agent-Oriented Software Engineering(AOSE'2000). Berlin:Springer-Verlag,2000.
[93]Arlow J, Neustadt I. UML和统一过程(实用面向对象的分析和设计)[M].北京：机械工业出版社,2003-02.
[94]李俊青,等.基于AUML的面向Agent的ERP系统设计[J],计算机工程与设计,2007,28(20)：5012-5017
[95]翁文勇,王泽兵,冯雁.UML技术在面向Agent系统分析中的应用研究[J].计算机工程与设计,2004,25(7)：1140-1142.
[96]吴文斌.一种面向Agent的分析与设计方法[J].小型微型计算机系统,2003,24(3)：456-459.
[97]王家伟,等.一种基于移动Agent的分布式信息检索优化模型[J].计算机科学,2008.35(7)：292-294
[98]赵龙文,侯义斌.智能软件：由面向对象到面向Agent[J].计算机工程与应用,2001(5)：41-43.
[99]张云勇,刘锦德.移动Agent技术[M].北京：清华大学出版社,2003.
[100]冯 锋.基于移动Agent的Web服务系统模型研究与构建[J],计算机技术与发展,2008.18(2)：247-250
[101]黄冬梅,等.基于移动Agent的W ebGIS体系结构[J],计算机应用与软件,2008.25(3)：56-58
[102]王栩.Agent系统通讯理论及组织结构的研究[D].中国科学院软科二研究所,2000
[103]游晓明,等.基于扩展UML的Agent建模语言的设计与研究[J],小型微型计算机系统,2006,27(3)：534-537
[104]Ruiz R. Maroto C. A Genetic Algorithm for Hybrid Flowshops with Sequence Dependent Setup Times and Machine Eligibility [J], European Journal of operational Research, 2006,169(3):781-800.
[105]邸向珍,赵守香.基于移动Agent的电子商务模型的研究与分析.北京工商大学学报(自然科学版),2009,27(5)：54-56
[106]肖丹丹,等.改进的蚁群算法在移动Agent迁移中的应用研究[J],成都大学学报,2008,27(1)：41-44
[107]骆正虎.移动Agent系统若干关键技术问题研究[D].合肥：合肥工业大学,2002.
[108]胡海洋,胡华,凌云.MAwA：基于移动Agent的一种高效可靠无线Web访问机制[J],计算机研究与发展,2008,45(4)：636-645
[109]E Pitoura, G Samaras. Data Management for Mobile Computing[M], Amsterdam, Netherlands:Kluwer Academic Publishers,1998
[110]J Jing, A S Helal. Client-server computing in mobile environments [J]. ACM Computing Survey,1999,31 (2):117-157
[111]徐沛娟.基于移动agent的分布式入侵检测系统研究[J],计算机应用研究,2009,26(10)：3898-3900
[112]马良,项培军.蚁群算法在组合优化中的应用[J].管理科学学报,2001,4(2)：32-37
[113]王万良.生产过程的智能调度方法及其应用[D].浙江：同济大学,2001
[114]李工农.基于非线性规划的组合优化算法[D].北京：中国科学院数学与系统科学研究院,2003
[115]Kendall, E. A. Agent roles and role models [EB/OL]. URL:http://www. labs. bt. com/Projects/ibsr/Papers/Patterns/iaipm. ps. gz,2002
[116]薛霄.面向Agent的软件设计开发方法[M],北京：电子工业出版社,2009
[117]高阳,江资斌.基于扩展UML的虚拟企业多Agent协作建模研究[J].制造技术与机床,2006,(2)：108-111
[118]Miao Kang, et. Modelling Mobile Agent Applications in UML 2.0 Activity Diagrams[C/OL], (04-04-21), http://www. auml. org/auml/supplements/UML2-AD. pdf
[119]James Odell, Marian Nodine, Renato Levy. FIPA Modeling:Agent Class Superstructure Metamode [C/OL], FIPA TC Modeling, (04-01-21), http://www. auml. org/auml/documents/CD2-03-10-31. doc
[120]毛国君,等.数据挖掘原理与算法[M],北京：清华大学出版社,2005
[121]Rehemujiang, et. Cooperative Multi-AGENT System in Diagnosing the WellDrilling Malfunction and Aceident Solving[J], Proceedings of the Seventh International Conference on CSCW in Design, September,2002, Rio de Janeiro, Brazil,:231-235.
[121]王汝传,徐小龙、黄海平,智能Agent及其在信息网络中的应用[M],北京邮电大学出版社,2006
[122]王曼君.集成化的集装箱码头管理信息系统[J]港口装卸,2001,4：25-27
[123]计三有,刘德鹏.集装箱码头交通运输组织建模及仿真技术研究[J].水运工程,2006,5：22-25
[124]马良,朱刚,宁爱兵,蚁群优化算法[M],科学出版社,2008.2
[125]黄红选,韩继业,数学规划[M],清华大学出版社,2006,3
[126]Botter R C. Stowage container planning:a model for getting an optimal solution[J]. IFIP Transaetion B:Computer Applications in Technology,1992, 5:217-229.
[127]Crainie T G, Gendreau M, Dejax P, Dynamic and stochastic models for the allocation of empty containers[J]. Operations Research,1993,41:102-126.
[128]Shen W S, Khoong C M. A DSS for empty container distribution planning [J]. Decision Support Systems,1995,5:75-82.
[129]Lai Y J, Hwang C L. Fuzzy Mathematical Programming[M]. Berlin:Springer Verleg, 1992.
[130]廖强,周凯,张伯鹏,基于现场总线的多Agent作业车间动态调度问题的研究[J].机械科学与技术.2000,21(4),757-760
[131]Kap Hwan Kim, Seung Hwan Won, Jae Kook Lim. An arehitectural design of Control software for automated container terminals [J], Computers& Industrial Engineering, 2004,46:741-754
[132]杨志新.集装箱码头业务管理信息系统的实践[J].交通与计算机,2005,23(2)：122-126
[133]DEGANO, et. "Multi-Agent Coordination and Collaboration for Controland Optimization Strategies in an Intermodal Container Terminal[C], IEEE InternationalEngineering Management Conference (IEMC-2002), Cambridge, UK, IEEE.
[134]Gambardella, et. Simulation and Planning of an intermodal container terminal[C], Simulation71(2):107 -116.
[135]REBOLLO, et.A Multi-Agent System for the Automation of a Port Container Terminal[C], Autonomous Agents 2000 workshop on Agents in Industry. Bareelona, Spain.
[136]Thurston, et, Distributed Agent Architecture Automation[J],26th International Computer Software and Conferenee,2002, Oxford, UK,:81-90.
[137]范中洲.大连智能虚拟港口[J].海事大学学报.2005,31(1)
[138]A. A. Shabayek, W. W. Yeung. A simulation model for the Kwai Chung container terminals In HongKong[J]. EuroPean Journal of Operational Research 2002:1-11
[139]樊晓平,罗熊,易晟,等.复杂环境下基于蚁群优化算法的机器人路径规划[J].控制与决策,2004,19(2)：166-170.
[l40]Poli Riccardo, Kennedy James, Blackwell Tim. Particle swarm optimization--an overview. Swarm Intell,2007(1):33-57.
[141]Ozcan E and Mohan CK. Analysis of a simple particle swarm optimization system. Intelligent Engineering Systems Through Artificial Neural Networks,1998,8:253-258.
[142]Ozcan E, Mohan C. Particle swarm optimization:surf ing the waves. In Proceedings of the IEEE congress on evolutionary computation(CEC 99),1999, pp.1939-1944.
[143]胡旺,李志蜀.一种更简化而高效的粒子群优化算法.软件学报,2007,18(4)：861-868.
[144]寇晓丽,刘三阳.一种随机微粒群混合算法求解约束优化问题.系统仿真学报,2007,19(10)：1248-2150.
[145]陈国初,俞金寿.单纯形微粒群优化算法及其应用[J].系统仿真学报,2006,18(4)862-865.
[146]Vis, et. Determination of the number of automated guided vehicles required at a semi-automated container terminal[J].Journal of the Operational Researeh Society,2001,52:409-417.
[147]杨杨,提高集装箱码头堆场使用率的问题研究[J],中国新技术新产品,2009(20)：81
[148]真虹.集装箱运输学[M].大连：大连海事大学出版1999
[149]Chen C Y, Hsieh T W. A Time-Space Network Model for the Berth Allocation Problem[C].19th IFIP TC6 Conference on System Modeling and Optimization, Cambridge, UK,1999,7.
[150]Hurink J, Juriseh B, Thole M. Tabu Search for Job-shop schduling Problem with Multipurpose Maehines[J]. OR Speektrum,1994,15(5):205-215
[151]熊一龙.基于移动Agent的无线webservice的技术研究[D].武汉理工大学,2009
[152]N. Pissinou, C. Dunu. A New Framework for Handling Mobile Clients in a Client-Server Database System[C]. The University of Southwestern Louisiana, Computer Communications,2000.5
[153]单国华.移动Agent数据保护的研究[D],合肥工业大学,2009
[154]魏登文.面向电子商务税收征管的移动Agent信任模型及其应用研究[D],华中科技大学,2009
[155]Evers J J M, Koppers S A J. Automated guided vehicle traffic control at a container terminal[J]. Transportation Researeh A,1996,30(1):21-34.
[156]Lai K K, Leung M. A Study of Gate Lane Allocation in Container Terminal [J]. Journal of Advanced Tansportation,1996,30(3):26-38
[157]Jiao, Ai-Ying. An empirical research of bohai rim container terminal based on PDEA model[J].2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008:1137-1141
[158]Legato P, Mazza R M. Berth Planning and resources optimization at a container terminal via discrete event simulation[J]. European Joumal of Operational Researeh,2001,133(3):537-547.
[159]Li. Modeling and simulation of container terminal logistics system[J].2009 2nd International Workshop on Knowledge Discovery and Data Mining, WKKD 2009:729-732
[160]Zhao, Hui. Research on container terminal scheduling system based on multi-agent[J]. Proceedings-2009 IITA International Conference on Control, Automation and Systems Engineering, CASE 2009:399-402
[161]Yan, Nannan. A multi-agent-based production dispatching information integration system for an automated container terminal[J]. Proceedings of the 2008 IEEE International Conference on Information and Automation, ICIA 2008:1117-1122
[162]Nguyen, Vu Duc. A dispatching method for automated lifting vehicles in automated port container terminals[J]. Computers and Industrial Engineering,2009,56(3): 1002-1020