摘要
近年,随着我国经济文化事业的快速发展和综合国力的进一步增强,我国举办的各类大型展览活动越来越多,例如广交会、世博会等,这些活动日益成为社会、企业和广大民众关注的焦点。大型展览活动参与人数多、社会反响大,一般具有人群密集性、人群不可预测性和人群分布不均匀性等特征,安全和服务问题突出。切实加强大型展览活动人群服务管理能力、预防和处理人群事故是达到高性能的安全保障和高质量的服务效果的重要内容。
以2010年上海世博会为契机,我国开始逐步加强大型展览活动人群服务管理体系的建设,中央和地方都根据各自的特征建立了相应的大型展览活动管理组织机构,全国性的人群服务管理体系框架已初步形成,并且在人群事故预防和人群服务实践中已经发挥着很重要的作用。然而,目前的人群服务管理体系的建设主要是从宏观层面进行的,它只能表明大型展览活动人群服务管理已经引起政府相关层面的重视。面对大型展览活动人群问题的突发性和不确定性,我国现有的人群服务管理体系在人群服务、人群事故的处置和管理上还存在着许多问题,难以有效地应对各种人群问题。必须从解决微观层面的问题尤其是难题入手,对相关的理论、技术和方法进行创新性地研究,给出最优的解决方案,从而全面提高我国大型展览活动人群服务管理水平。
本文综合通信和计算机科学、管理科学、运筹学等学科,集成移动通信、情景感知、系统仿真等技术,系统地研究大型展览活动人群智能服务管理问题,揭示人群服务管理中微观和宏观层面之间的内在联系,探索大型展览活动人群智能服务管理规律和机理。根据游客参观全过程的服务需求分析,从参观计划、参观协调、服务保障和应急反应的决策问题着手,研究了大型展览活动人群智能服务管理中的微观层面的关键问题。各章主要内容如下：
第一章绪论,介绍了本文的研究背景、研究内容、研究意义及论文结构。第二章文献综述,概括了大型展览活动人群智能服务管理相关概念,从情景感知系统在游览活动中的应用、人群运动和大型展览活动人群服务运营三个方面对大型展览活动人群智能服务管理的相关研究进行了综述,并在此基础上,进行了简要的评述,指出了目前大型展览活动人群服务管理的研究不足。
第三章,从系统论的角度研究了大型展览活动人群智能服务管理问题。首先,提出了大型展览活动人群智能服务系统的定义,介绍了系统的基本维度,包括系统的要素、系统的目标、系统的结构、系统的状态和系统的环境,阐述了系统信息感知与发布技术。然后,提出需要深入研究的系统控制与优化问题,并且建立了大型展览活动服务准备、服务实施和应急控制三位一体面向全过程的综合服务运营管理体系。最后,在人群服务需求分析的基础上设计了大型展览活动人群智能服务决策支持系统,概述了系统的整体结构,介绍了系统的主要功能,并提出了系统数据库的设计构想。
第四章,从游客参观行程计划的角度研究了时问依赖网络中游客个性化参观行程设计问题。考虑到人群拥挤、突发事件和道路类型对出行时间的影响,提出了基于离散时间的时间序列图模型,通过时间序列图模型表示交通网络中不同时间不同路段的出行时间。在此基础上,提出了两种既符合大型展览活动交通实际,又符合游客个人偏好的参观行程设计方案,即满足游客单日和多日参观计划需求约束下的最优行程设计,分别建立了相应的混合整数规划模型,设计了基于网络计划和动态规划思想的标号算法。
第五章,从游客参观协调的角度研究了基于Multi-agent的人群服务协调控制问题。首先,设计了基于Multi-agent的人群智能服务系统,概述了系统的基本结构,详细介绍了Multi-agent系统的建模思路。然后,提出了多阶段动态协调控制方法,该方法在引入帕累托最优概念的基础上,通过游客总体满意度下的择优选择机制为游客实时动态的决定下一参观目标点的选择,使用Logit模型进行参观路线的选择。最后,以上海世博会为背景,设计了基于Multi-agent系统的仿真试验和三种对比方案,对协调控制方法进行了检验和灵敏度分析。
第六章,从服务保障的角度研究了大型展览活动移动资源调度问题。介绍了移动资源调度工作的概念模型,总结了移动资源调度的过程。在此基础上,针对大型展览活动中服务资源需求的多样性和预测的资源需求情形,研究了考虑未来需求的多资源调度问题,建立了基于期望成本的多资源调度模型,基于图论中网络优化和线性规划优化思想,设计了多资源分类调度的启发式算法,并分析了算法复杂性。
第七章,从突发事件应急反应的角度研究了大型展览活动人群疏散问题。介绍了大型展览活动中的突发事件,分析了突发事件的特征,对人群事故发生机理进行了初步的探索。考虑到大型展览活动突发事件应急疏散时,常常出现多源点同时需要疏散,且有多个疏散汇点的情形,研究了多源多汇和有容量限制条件下的应急疏散问题,建立了基于路径的网络流控制疏散模型,设计了基于关键优选路径进行网络流控制的启发式算法,并分析了算法的复杂性。
最后,在结论部分,对论文的工作进行了总结,并对未来的研究加以展望。
In recent years, as the rapid development of China's economic and cultural undertakings and further enhancement of China's overall national strength, various large-scale exhibitons organized by China are increasing, e.g. Chinese Export Commodities Fair and World Expo. These exhibitons are increasingly becoming the focus of attention paid by society, businesses and the general public. Large-scale exhibitons have a large number of participants and great social repercussions. The crowd's characteristics of the large-scale exhibitons are intensive, unpredictable and uneven distribution. So, security and service issues are very obvious. It becomes an urgent task to enhance the ability of crowd's service management, prevent and deal with crowd incidents so as to achieve high-performance security and high-quality service.
Taking 2010 Shanghai World Expo as an opportunity, China has gradually built the crowd service management system for large-scale exhitions with the establishment of respective organizations in charge of crowd service management in national,provice and city levels.The national crowd service management system of large-scale exhibitons has begun to take shape and play an important role in practice. However, since the current crowd service management system is designed at macro level, it is far from the practical need at the micro level. The theory, technologies and methods at the micro level are the base of the whole crowd service management system. We should focus on the research in micro-level problems especially difficult problems. Further study on revelent theory, technologies and methods will surely provide an optimal solution so as to improve the overall crowd service management level of Chinese large-scle exhibitons.
This dissertation employs multiple research methods including communication and computer science, management science and operations research, etc. and integrates a lot of technologies, such as mobile communicaition, context aware and system simulation. It is aimed to systematically study the crowd intelligent service management issues of large-scale exhibitons, unveil the inner correlation between the micro and macro levels, and finally provide new perspective and decision support for crowd intelligent service management of large-scale exhibitions in the future. According to analysis of tourist service demand in the whole trip, based on the decision-making problems in the process of crowd service management including travel plan, travel coordination, service security and emergency response, this dissertation studys the micro-level key problems involved in crowd intelligent service management of large-scale exhitions. The main contents of this dissertation are as follows:
In chapter 1,the research background, contents and significance have been introduced together with the structure of the dissertation. In chapter 2,literature review is made to summarize the concepts related to crowd intelligent service management in large-scale exhibitions, and cover the research conducted from three aspects:applications of context-aware systems in travel activities, crowd movement and crowd service operations in large-scale exhibitions. Furthermore, we commentate on the previous research and point out the deficiency in the current research on crowd service management in large-scale exhibitions.
In chapter 3,this dissertation studies the crowd intelligent service management in large-scale exhibitions from the perspective of system theory. Firstly, we propose the definition of crowd intelligent service system for large-scale exhibitions, and introduce the system's basic dimensions including system elements, objectives, structure, status and environment. System information awareness and release technologies are also introduced. Then, this dissertation gives the system control and optimization problems deserved to be studied deeply with the establishment of the whole process-oriented integrated service operation management system including three levels of large-scale exhibitions:service reserve, service implementation and emergency control.Finally, based on the analysis of crowd service needs, crowd intelligent service decision-making system for large-scale exhibitons is designed. The whole systematic organization is illustrated. The main functions and a blueprint for system database design are introduced.
In chapter 4, this dissertation mainly focuses on personalized tourist trip design based on time-dependent network from the perspective of tourist trip plan. Taking into account the impact of such factors as crowd congestion, emergency, and road types on travel time, we propose a time-series graph model based on discrete time. The travel time in transport network in different sections and different time is represented using the time-series graph model. On this basis, we propose two trip design methods which are consistent with the current traffic and tourist personal preference in large-scale exhibitions, that is, one-day tourist trip design method and multi-day tourist trip design method. Then, we respectively establish the mixed integer programming models and design labeling algorithms based on the idea of network planning and dynamic programming.
In chapter 5, crowd service coordination and control based on multi-agent is considered from the perspective of travel coordination. Firstly, crowd intelligent service system based on multi-agent is designed, the whole systematic organization is illustrated, and the ideas of modeling the multi-agent system are introduced in detail. Moreover, we propose a multi-stage dynamic coordination and control method. Through introducing the concept of Pareto Optimality, this method decides the next visiting node in real time and dynamically for tourists based on preferential selection mechanism to total tourist satisfaction value, and selects roads using Logit model. Finally, under the background of Shanghai World Expo, multi-agent system simulation and three different methods are designed, the coordination and control methods are tested, and sensitivity analysis is also making.
In chapter 6, mobile resource scheduling problem of large-scale exhibition is investigated from the perspective of service security. We introduce a conceptual model of mobile resource scheduling work, and give the process of mobile resource scheduling. On this basis, due to the diversity of service resources and forecast of resource demands, this chapter studies the multi-resource scheduling problem considering future demand, and establishes a multi-resource scheduling model based on expectation cost. Furthermore, a novel heuristic algorithm based on network optimization in graph theory and linear programming optimization is given in terms of multi-resource classification. The computational complexity of the algorithm is also analyzed.
In chapter 7, crowd evacuation of large-scale exhibitions is considered from the perspective of emergency response. We introduce the emergent incidents in large-sclae exhibitions, analyze the characteristics of the incidents, and start a preliminary study to mechanism of crowd incidents. Then, we study the emergency multi-source and multi-destination evacuation problem with the capacity constraints, and propose a path-based network flow control evacuation model. A novel heuristic algorithm of network flow control is designed based on key selected path. The computational complexity of the algorithm is also analyzed.
In the conclusion, we pointed out the main innovation of the dissertation and the perspective for the further research.
引文
[1]Adam B. Time and social theory [M]. Philadelphia:Temple University Press,1990.
[2]Adler J.L. Investigating the learning effects of route guidance and traffic advisories on route choice behavior [J].Transportation Research Part C,2001,9:1-14.
[3]Ahuja R.K., Magnanti T.L.,and Orlin J.B.Network flows:theory, algorithms, and applications [M].Prentice Hall,1993.
[4]Aoki T.The simulation system of passenger flow[R].Quarterly Review of Rail Technical Research Institute 1994,35(2).
[5]Archetti C., Hertz A., Speranza M. Metaheuristics for the team orienteering problem [J]. Journal of Heuristics,2007,13:49-76.
[6]Bakuli D.,Smith M.G. Resource allocation in state-dependent emergency evacuation networks [J].European Journal of Operational Research,1996,89:543-555.
[7]Baldauf M.,Dustdar S.,and Rosenberg F. A survey on context-aware systems [J].Int. Journal of Ad Hoc and Ubiquitous Computing,2007,2(4):263-277.
[8]Bazaraa M.S., Jarvis J.J.,and Sherai H.D.Linear programming and network flows,2nd Edition [M].John Wiley and Sons, New York, NY,1990.
[9]Bekhor S.,Ben-Akiva M.E.,Ramming M.S.Adaptation of Logit Kernel to Route Choice Situation [J].Transportation Research Record,2002,1805:78-85.
[10]Bertsimas D.and Tsitsiklis J.N.Introduction to linear optimization [M].Athena Scientific, 1997.
[11]Bieber G. and Giersich M. Personal mobile navigation systems - design considerations and experiences [J].Computers and Graphics,2001,25(4):563-570.
[12]Blue V.J., Adler J.L. Cellular automata microsimulation for modeling bi-directional pedestrian walkways [J].Transportation Research Part B,2001,35:293-312.
[13]Brown P.J.Triggering information by context [J].Personal Technologies,1998,2(1):1-9.
[14]Burcaw G. E. Introduction to museum work [M].Nashville:American Association for State and Local History,1997.
[15]Burns J.P. and Mules T.J.A framework for the analysis of major special events[J].The Center for South Australian Economic Studies, Adelaide,1986, pp 5-38
[16]Butt S.,Cavalier T. A heuristic for the multiple tour maximum collection problems [J]. Computers and Operations Research,1994,21:101-111.
[17]Campos V.B.G.,Silva P.A.L.,Netto P.O.B.Evacuation transportation planning:a method of identifying optimal independent routes [C].Surcharov L J.Proceedings of Urban Transport Ⅴ:Urban Transport and the Environment for the 21st Century. Southampton: WIT Press,2000:555-564.
[18]Casademont J., Lopez-Aguilera E., Paradells J., et al. Wireless technology applied to GIS[J].Computer & Geosciences,2004,30:671-682.
[19]Chalmet L., Franis R., Saunders P. Network model for building evacuation [J]. Management Science,1982,28:86-105.
[20]Chao I., Golden B., Wasil E. A fast and effective heuristic for the orienteering problem [J]. European Journal of Operational Research,1996,88:475-489.
[21]Chao I., Golden B., Wasil E. A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions [J]. American Journal of Mathematical and Management Sciences,1993,13(3-4):371-406.
[22]Chao I., Golden B., Wasil E. Theory and methodology-the team orienteering problem [J]. European Journal of Operational Research,1996,88(3):464-474.
[23]Chen G. and Kotz D. A survey of context-aware mobile computing research[R]. Tech. Rep. TR2000-381, Dartmouth, November 2000.
[24]Christoph G. Mobile tourist guides-Evaluation of the state of the art and development of a light-weight framework for location-based services [D]. Vienna:Vienna University, 2005.
[25]Dantzig G., Ramser J. The truck dispatching problem [J]. Managment Science,1959, (6):80-91.
[26]Desrochers M., Desrosiers J., Solomon M. A new optimization algorithm for the vehicle routing problem with time windows [J]. Operations Research,1992,40(2):342-354.
[27]Dey A.K. Understanding and using context [J]. Personal and Ubiquitous Computing, 2001,5(1):4-7.
[28]Erwig M. Graphs in spatial databases [D]. PhD thesis, Fern University at Hagen,1994.
[29]Erwig M., Guting R.H. Explicit graphs in a functional model for spatial databases [J]. IEEE Transactions on Knowledge and Data Engineering,1994,6(5):787-804.
[30]Farahmand M., Garetto C., Bellotti E., et al. Monte Carlo simulation of electron transport in the Ⅲ-nitride wurtzite phase materials system:binaries and ternaries [J], IEEE Transactions on Electron Devices,2001,48(3):535-542.
[31]Feillet D., Dejax P., Gendreau M. Travelling salesman problems with profits [J]. Transportation Science 2005,39:188-205.
[32]Fiedrich F., Gehbauer F., Rickers U. Optimized resource allocation for emergency response after earthquake disasters [J]. Safty Science.2000,30:41-57.
[33]Finin T., Labrou Y., Meyeld J. KQML as an Agent Communication Language [J]. In Bradshaw, J.M. (eds.):Software Agents, MIT Press,1997,291-316.
[34]Fischetti M., Gonzalez J.J.S., Toth P. A branch-and-cut algorithm for the symmetric generalized traveling salesman problem [J]. Operations Research,1997,45(3):378-394.
[35]Fischetti M., Salazar J., Toth P. Solving the orienteering problem through branch-and-cut [J]. INFORMS Journal on Computing,1998,10:133-148.
[36]Fisher M.L. Optimal solution of vechicle routing problems using minimum k-trees [J]. Operations Research,1994,42(4):141-153.
[37]Fruin J. Pedestrian and planning design [M]. Metropolitan Association of Urban Designers and Environmental Planners,1971.
[38]Gendreau M., Laporte G., Semet F. A branch-and-cut algorithm for the undirected selective travelling salesman problem [J]. Networks,1998a,32:263-273.
[39]Gendreau M., Laporte G., Semet F. A tabu search heuristic for the undirected selective travelling salesman problem [J]. European Journal of Operational Research,1998b,106: 539-545.
[40]George B. and Shekhar S. Time aggregated graphs:a model for spatio-temporal network [J]. Journal on Data Semantics Ⅺ,2008,11:191-212.
[41]Getz D. Event management and event tourism [M]. New York:Cognizant Communications Corporation,1997.
[42]Givens G.G. Disaster duty-prepare to evacuate, prime for alert [J]. Traffic digest and review,1963,11:4-7.
[43]Golden B., Levy L., Vohra R. The orienteering problem [J]. Naval Research Logistics,1987,34:307-318.
[44]Golden B., Wang Q., Liu L. A multifaceted heuristic for the orienteering problem [J]. Naval Research Logistics,1988,35:359-366.
[45]Gunn C. Amendment to Leiper:the framework of tourism [J]. Annals of Tourism Research,1980,7:253-255.
[46]Gupta A.K., Yadav P.K. SAFE-R:a new model to study the evacuation profile of a building [J]. Fire Safety Journal,2004,39(7):539-556.
[47]Haghani A., Oh S.C. Formulaiton and solution of a multi-commodity, multi-modal network flow model for disaster relief operations [J]. Transprotion Research Part A,1996, 30:231-250.
[48]Hall C. Hallmark tourist events:impacts, management and planning [M]. John Wiley and Sons Ltd,1992
[49]Hamacher H.W., Tjandra S.A. Earliest arrival flow model with time dependent capacity for solving evacuation problems[C]. Pedestrian and evacuation dynamics, edited by Michael S, Som D S, Berlin:Springer-Verlag,2002,267-276.
[50]Hamacher H.W., Tjandra S.A. Mathematical modeling of evacuation problems-a state of the art [M]. Pedestrian and evacuation dynamics, Berlin:Springer-Verlag,2002,227-266.
[51]Hamre T. Development of semantic spatio-temporal data models for integration of remote sensing and in situ data in marine information system [D]. PhD thesis, University of Bergen, Norway,1995.
[52]Helbing D. A fluid dynamic model for the movement of pedestrians [J].Complex Systems, 1999,6:391-415.
[53]Helbing D., Buzna L., Johansson A., and Werner T. Self-Organized pedestrian crowd dynamics:experiments, simulations, and design solutions [J]. Transportation Science, 2005,39(1):1-24..
[54]Helbing D., Farkas I., Vicsek T. Simulating dynamical features of escape panic [J]. Nature,2000,407:487-490.
[55]Helbing D. and Molnar P. Social force model for pedestrian dynamics [J]. Physical Review,1995,51(5):4282-4285.
[56]Henderson L. F. The statistics of crowd fluids [J]. Nature,1971,229:381-383.
[57]Henderson L. F. Sexual differences in human crowd motion [J]. Nature,1972,240: 353-355.
[58]Hillier F.S., Lieberman G.J. Introduction to Operations Research [M]. New York: McGraw-Hill. Inc.,1990.
[59]Hoogendoom S., Bovy P.H.L. Gas-kinetic modeling and simulation of pedestrian flows [J].Transportaion Research Record,2000,1710:28-36.
[60]Huang Y., Bian L. A Bayesian network and analytic hierarchy process based personalized recommendations for tourist attractions over the Internet[J].Expert Systems with Applications,2009,36(1):933-943.
[61]Hughes R.L. The flow of large crowds of pedestrians [J].Mathematics and Computers in Simulation,2000,53(4-6):367-370.
[62]Hughes R.L. A continuum theory for the flow of pedestrians [J].Transportation Research Part B,2002,36:507-535.
[63]Huijnen C. Mobile tourism and mobile government-an inventory of European projects[R]. Technical report, European Center for Digital Communiction (EC/DC),2006.
[64]Ichoua S., Gendreau M., Potvin J.Y. Vehicle dispatching with time-dependent travel times [J].European Journal of Operational Research,2003,144(2):379-396.
[65]Jae Y.C. Stochastic scheduling problems for minimizing tardy jobs with application to emergency vehicle dispatching on unreliable road networks [D]. New York:University of New York,2003:61-68.
[66]Jung S. A genetic algorithm for vehicle routing problem with time dependent travel times [D].University of Maryland at College Park, College Park, MD, USA,2000.
[67]Kataoka T., Kawamura H., Kurumatani K., and Ohuchi A. Distributed visitors coordination system in Theme Park Problem [C]. Massively Multi-Agent Systems I, First International Workshop, MMAS 2004, Kyoto, Japan, December 10-11,2004, Revised Selected and Invited Papers:335-348.
[68]Katerina K. Personalizing recommendations for tourists[J].Telematics and Informatics, 2009, doi:10.1046/j.tele.2009.05.003
[69]Kaufman D.E., Smith R.L.Fastest paths in time-dependent networks for intelligent vehicle highway systems applications [J]. IVHS Journal,1993,1(1):1-11.
[70]Kawamura H., Kataoka T., Kurumatani K., Ohuchi A. Investigation of global performance effected by congestion avoiding behavior in Theme Park Problem [J]. IEEE Transaction EIS,2004,124(10):1922-1929.
[71]Kawamura H., Kurumatani K. and Ohuchi A. Modeling of Theme Park Problem with Multiagent for Mass User Support [C].Multiagent for Mass User Support, First International Workshop, MAMUS-03 Acapulco, Mexico, August 2003,pp48-69.
[72]Ke L., Archetti C., Feng Z. Ants can solve the team orienteering problem [J]. Computers & Industrial Engineering,2008,54:648-65.
[73]Kirchner A., Schadschneider A. Simulation of evacuation process using a bionics-inspired cellular automaton model for pedestrian dynamics [J]. Physica A,2002, 312(1-2):260-276.
[74]Kramer R., Modsching M., and ten Hagen K. A city guide agent creating and adapting individual sightseeing tours based on field trial results [J]. International Journal of Computational Intelligence Research,2006.2(2):191-206.
[75]Kray C. and Baus J. A survey of mobile guides[C]. Proceedings of HCI in Mobile Guides (Udine, Italy:in conjunction with Mobile HCI 2003).
[76]Kurumatani K. Mass user support by social coordination among citizens in a real environment [C]. Multiagent for Mass User Support, First International Workshop, MAMUS-03 Acapulco, Mexico, August 2003:1-17.
[77]LaporteG, Martello S. The selective travelling salesman problem [J]. Discrete Applied Mathematics,1990,26:193-207.
[78]Lew A. A framework of tourist attraction research [J]. Annals of Tourism Research,1987, 14:533-575.
[79]Lin Y.C., Hwang K.S. A mixed-coding scheme of evolutionary algorithms to solve mixed-integer nonlinear programming problems [J]. Computers and Mathematics with Applications,2004,47(8):1295-1307.
[80]Lorenzi F., Dos Santos F., Ferreira Jr. Optimizing preferences within groups:a case study on travel recommendation [J]. Lecture Notes in Computer Science,2008.
[81]Lovas G.G. Modeling and simulation of pedestrian traffic flow [J]. Transportation Research B,1994,28 (6):429-443.
[82]Lu Q.S. Capacity constrained routing algorithms for evacuation route planning [D]. PhD thesis, University of Minnesota,2006.
[83]Malandraki C., Daskin M.S. Time dependent vehicle routing problems:formulations, p roperties and heuristic algorithm s [J]. T ransportation Science,1992,26 (3).
[84]Martello S. and Toth P. Knapsack Problems-algorithm and computer implementations [M]. John Wiley & Sons. New York, NY, USA,1990.
[85]Maruyama A., Shibata N., Murata Y, Yasumoto K., and Ito M. A personal tourist navigation system to support travelling multiple destinations with time restrictions[C].18th International Conference on Advanced Information Networking and Applications,2004.
[86]Mingozzi A., Bianco L., Ricciardelli S. Dynamic programming strategies for the traveling salesman problems with time windows and procedence constraints[J]. Operations Research,1997,45(3):365-377.
[87]Mitchell D.H, Smith J.M. Topological Network Design of Pedestrian Networks [J]. Transportation Research Part B,2001,35:107-135.
[88]Montane F., Galvao R. A tab search algorithm for the vehicle routing problem with simultaneous pick-up and deliveries [J]. Computers&Operations Research,2006, 33(3):595-619.
[89]Mullins R. Mobile service platformas cluster[R]. White paper:Context and Knowledge Management. DG Information Society&Media,2008.
[90]Munuera J., Ruiz S. Trade fairs as services:a look at visitors'objectives in Spain [J], Journal of Business Research,1999,44(1):17-24.
[91]Muramatsu M., Nagatani T. Jamming transition in two-dimensional pedestrian trafic [J]. Physica A,2000:275281-291.
[92]National Task Force on Tourism Data[R], Final Report, Statistics Canada, Ottawa,1989.
[93]Niaraki A.S., Kim K. Ontology based personalized route planning system using a multi-criteria decision making approach [J]. Expert Systems with Applications,2009,36: 2250-2259.
[94]Okazaki S., Matsushita S. A study of simulation model for pedestrian movement with evacuation and queuing [C]. Inc:Proceedings of the international conference on engineering for crowd safety,1993:271-280.
[95]Orlikowski W.J. and Yates J. It's about time:temporal structuring in organizations [J].Organization Science,2002,13(6):684-700.
[96]Ozdamar L.,Ekinci E. Emergency logistics planning in natural disasters [J].Annals of Operations Research,2004:217-245.
[97]Pateli A.G., Giaglis G.M., Spinellis D.D. Wireless value-added services in exhibition shows [J]. International Journal of Mobile Communications,2006,4(2):193-209.
[98]Peponis J.,Dalton R.C.,Wineman J.,Dalton N. Measuring the effects of layout upon visitors'spatial behaviors in open plan exhibiton settings [J].Environment and Planning B: Planning and Design,2004,31:453-473.
[99]Pisinger D.,Ropke S. A general heuristic for vehicle routing problems [J].Computers and Operations Research,2007,34 (8):2403-2435.
[100]Po-Han Chen, Feng Feng. A fast flow control algorithm for real-time emergency evacuation in large indoor areas [J].Fire Safety Journal,2009,44(5):732-740.
[101]Prado J.E.,Wurman P.R. Non-cooperative planning in multi-agent, resource-constrained environments with markets for reservations [R].Working Note of the AAAI-02 Workshop on Planning with and for Multiagent Systems, Technical Report WS-02-12, AAAI Press, 2002,pp.60-66.
[102]Ramesh R., Brown K. An efficient four-phase heuristic for the generalized orienteering problem [J].Computers and Operations Research,1991,18:151-165.
[103]Ramesh R.,Yoon Y.,Karwan M. An optimal algorithm for the orienteering tour problem [J].ORSA Journal on Computing,1992,4:155-165.
[104]Raptis D.,Tselios N.,Avouris N. Context-based design of mobile applications for museums:a survey of existing practices[C].The 7th International Conference on Human Computer Interaction with Mobile Devices & Services, Salzburg, Austria 2005,pp.153-160.
[105]Reichenbacher T. Mobile cartography-adaptive visualisation of geographic information on mobile devices [J].Verlag Dr. Hut, Miinchen,2004, ISBN 3-89963-048-3.
[106]Renaud J.,Laporte G.,Boctor F. A tabu search heuristic for the multi-depot vehicle routing problem [J].Computers and Operations Research,1996,23 (3):229-235.
[107]Renegar J. A polynomial time algorithm based on Newton's method for linear programming [J].Mathematical Programming,1988,40,59-93.
[108]Salvador C.P.,Federico G.G. Optimal building evacuation time considering evacuation routes [J].European Journal of Operational Research,2009,192(2):692-699.
[109]Sashima A.,Izumi N.,and Kurumatani K. CONSORTS:A multiagent architecture for service coordination in ubiquitous computing [C].Multiagent for Mass User Support, First International Workshop, MAMUS-03 Acapulco, Mexico, August 2003,pp.190-216.
[110]Schilit B.,Theimer M. Disseminating active map information to mobile hosts [J].IEEE Network,1994:8(5):22-32.
[111]Schwinger W.,Grunl C.h.,Proll B.,Retschitzegger W.,Schauerhuber A. Context-awareness in mobile tourism guides-a comprehensive survey[R].Technical Report,Johannes Kepler University Linz, IFS/TK,2005.
[112]Shekhar S.,Chawla S.Spatial databases:tour [M].Prentice-Hall, Englewood Cliffs, 2003.
[113]Sherali H.D.,Subramanian S.Opportunity cost-based models for traffic incident response problems [J].Journal of Transportation Engineering,1999,125,176-185.
[114]Soe Y.M.,Myo M.N.,Ni L.T. RPCF algorithm for multi-agent tourism system[C].In: 2006 IEEE International Symposium on Micro-Nano Mechanical and Human Science, MHS,2006. (Article number 4110418).
[115]Souffriau W., Vansteenwegen P.,Vanden Berghe G.,Van Oudheusden D.A path relinking approach for the team orienteering problem [J].Computers & Operations Research,2009,doi:10.1016/j.cor.2009.05.002
[116]Souffriau W, Vansteenwegen P and Vertommen J.,et al.A personalized tourist trip design algorithm for mobile tourist guides [J].Applied Artificial Intelligence,2008, 22(10):964-985.
[117]Stephens S.,Rung J.,Lopez X. Graph data representation in oracle databese10g:Case studies in life sciences [J].IEEE Data Engineering Bulletin,2004,27(4):61-66.
[118]Tang H.,Miller-Hooks E.A tabu search heuristic for the team orienteering problem [J]. Computer and Operations Research,2005,32:1379-1407.
[119]Thompson P.A., Marchant E.W. A computer model the evacuation of large building populations [J].Fire Safety Journal,1995,24:131-148.
[120]TRB.Highway capacity manual 2000[M].Transportation Research Board, Washington, DC.2000.
[121]Tsiligirides T. Heuristic methods applied to orienteering [J].Journal of Operational Research Society 1984,35:797-809.
[122]Vansteenwegen P.,Souffriau W.,Vanden Berghe G.,Van Oudheusden D. A guided local search metaheuristic for the team orienteering problem [J].European Journal of Operational Research,2009,196(1):118-27.
[123]Vansteenwegen P.,Souffriau W.,Vanden Berghe G.,Van Oudheusden D.Metaheuristics for tourist trip planning [J].Metaheuristics in the Service Industry. In:Lecture notes in economics and mathematical systems,2009, vol.624. Berlin:Springer; to appear (ISBN: 978-3-642-00938-9).
[124]Vansteenwegen P.,Van Oudheusden D. The mobile tourist guide:an OR opportunity [J]. OR Insights2007,20(3):21-27.
[125]Verhaar J.,Meeter H. Project model exhibitions [M].Reinwardt Academie,1989. [126] Want R.,Hopper A.,Falcao V. et al. The active badge location system [J].ACM Transactions on Information Systems,1992,10(1):91-102.
[127]Watts J.M. Computer models for evacuation analysis [J].Fire Safety Journal,1987,12: 237-245.
[128]Weiser M.The computer for the twenty-first century [J].Scientific American,1991, 265(3):94-104.
[129]Werthner H.,Klein S.Information technology and toursim-a challenging relationship[M],Springer, Wien, New York,1999.
[130]Wolfram S.Cellular automata and complexity [M].Baltimore:Addison-Wesley Publishing Company,1994.74-75.
[131]Wren A.,Holliday A. Computer scheduling of vehicles from one or more depots to a number of delivery points [J].Operational Research Quarterly,1972,23:333-344.
[132]Xu G.Y.,Shi Y.C.,Xie W.K. Pervasive/Ubiquitous computing [J].Chinese Journal of Computer,2003,26(9):1042-1050.
[133]Yang L.Z.,Zhao D.L.,Li J. and Fang T.Y.Simulation of the kin behavior in building occupant evacuation based on Cellular Automaton [J].Building and Environment,2005, 40(3):409-413.
[134]Yang L.Z.,Zhao D.L.,Li J.,Fang W.F.,Fan W.C.Simulation of evacuation behaviors in fire using spacial grid[J].Progress in Natural Science,2004,14(7):614-618.
[135]Yamashita T.,Izumi K.,and Kurumatani K. Effect of using route information sharing to reduce traffic congestion [C].Multiagent for Mass User Support, First International Workshop, MAMUS-03 Acapulco, Mexico,August 2003,pp.86-104.
[136]Yu W.J.,et al.Centrifugal force model for pedestrian dynamics [J].Physical Review E, 72,026112,2005.
[137]Zheng W.,Yuan Y.Identifying the differences between stationary office support and mobile work support:a conceptual framework. Int. J.Mobile Communications,2007, 5(1):107-122.
[138]阿尔弗雷德·海勒著,吴惠族等译.文明的进程世博会的发展与思考[M].上海：上海科学技术文献出版社,2003.
[139]阿尔诺·勃兰特等著,任树银等译.汉诺威世博会对区域经济的影响[M].上海：科技文献出版社,2003.
[140]贝塔朗菲.科学学译文集[M].科学出版社,1981.
[141]陈大为.世博会微观系统中关于人流和以人流为基础的物流系统研究[D].华东师范大学硕士学位论文,2006.
[142]陈鹏.基于多智能主体的人群流动形态动态模拟研究[D].同济大学博士学位论文,2006.
[143]陈迅.上海世博会管理策略研究[J].上海管理科学,2006,(2)：17-19.
[144]崔洪军.大型活动交通组织管理关键技术研究[D].东南大学博士学位论文,2006.
[145]崔晓文.国际展览业概貌[EB/OL]. http://www.istis.sh.cn/list/list.aspx?id=4471.[2009-10-2]
[146]戴更新,达庆利.多资源组合应急调度问题的研究[J].系统工程理论与实践,2000,(9)：52-55.
[147]刁在筠,刘桂真,宿洁,马建华.运筹学(第三版)[M].北京：高等教育出版社,2007.
[148]方颖.上海世博会人员流动均衡管理的研究[D].上海交通大学硕士论文,2007.
[149]方正,陈大宏,张铮,卢兆明.建筑物火灾人员疏散的计算机仿真[J],计算机仿真,2001,18(2)：49-52.
[150]冯志斌,孙超.关于大型社会经营活动安全问题的探讨[J].中国安全科学学报,2006,16(9)：119-123.
[151]高明霞,贺国光.考虑交叉口特性的疏散交通路线研究[J].土木工程学报,2007,40(6)：80-83.
[152]高淑萍,刘三阳.基于联系数的多资源应急系统调度问题[J].系统工程理论与实践,2003,(6)：113-122.
[153]顾爱怡.会展在中国经济发展中的作用、问题及对策[J].商业时代,2008,(29)：85-86.
[154]顾加额.大型社会性公众活动应急预案研究[D].上海交通大学硕士论文,2006.
[155]顾君忠.情景感知计算[J].华东师范大学学报(自然科学版),2009,(5)：1-20.
[156]郭强,谢秉磊.随机旅行时间车辆路径问题的模型及其算[J].系统工程学报,2003,18(3)：244-247.
[157]国务院.大型群众性活动安全管理条例[EB/OL]. http://www.gov.cn/jrzg/2007-09/21/content 758108.htm.[2009-12-20]
[158]郭耀煌,谢秉磊.一类随机动态车辆路径问题的策略分析[J].管理工程学报,2003,17(4)：114-115.
[159]何建敏,刘春林,尤海燕.应急系统多出救点的选择问题[J].系统工程理论与实践,2001,(11)：89-93.
[160]何清华,李永奎,乐云.上海2010年世博会信息化集成与管理系统研究[J].同济大学学报(自然科学版),2007,35(6)：856-860.
[161]胡志莹，叶明海.大型社会活动人群拥挤事故防范系统研究[J].灾害学,2006,21(1)：108-112.
[162]克劳德·塞尔旺(美),竹田一平(日).国际级博览会影响研究[M].上海：上海科学技术文献出版社,2003.
[163]李成,云美萍,杨晓光.日本爱知世博会的交通管理对策[J].城市交通,2007,4(2)：19-24.
[164]李进,朱道立.基于multi-agent的大型人群活动多阶段动态协调控制模型[J],中国管理科学,2009,17(5)：113-119.
[165]李金华,朱道立.基于nulti-agent的大型会展活动的游客协调控制方法[J],系统工程学报,2009. (In press).
[166]李军.有时间窗的车辆路线安排问题的启发式算法[J].系统工程,1996,14(5)：45-50.
[167]李军,郭强,刘建新.组合运输的优化调度[J].系统工程理论与实践,2001,(2)：117-121.
f168]李克平.2010年上海世博会客流预测分析[J].交通与运输,2005,(1)：21-22.
[169]李清海.上海世博会经济分析——兼论德国2000年汉诺威世博会[J].同济大学学报(社会科学版),2004,15(1)：18-23.
[170]刘春林,何建敏,盛昭瀚.多出救点应急系统最优方案的选取[J].管理工程学报,2000,14(1)：13-15.
[171]刘大可.中国会展业：理论、现状与政策[M].中国商务出版社,2004.
[172]卢春霞.人群流动的波动性分析[J].中国安全科学学报,2005,2：30-34.
[173]卢春霞.拥挤人群中的挤压分析[J].交通运输系统工程与信息,2007,4：98-103.
[174]陆君安,方正,卢兆明,赵春梅.建筑物人员疏散逃生速度的数学模型[J],武汉大学 学报(工学版),2002(2)：66-70.
[175]吕永波,贾楠,任锦鸾等.救灾物资发放问题的动态遗传算法求解[J].管理科学学报,2008,11(3)：29-34.
[176]马寿峰,李艳君,贺国光.城市交通控制与诱导协调模式的系统分析[J].管理科学学报,2003(6),6(3)：71-78.
[177]马寿峰,卜军峰,张安训.交通诱导中系统最优与用户最优的博弈协调[J].系统工程学报,2005,20(1)：30-37.
[178]马征.公众聚集场所人员安全疏散性能化设计与评价[D].西安：西安建筑科技大学,2004
[179]潘海啸,崔宁,刘冰.2010年上海世博会交通全过程需求管理框架[J].城市规划学刊,2006,(4)：53-60.
[180]钱世超,李英.经济管理系统模拟——理论与方法[M].北京：化学工业出版社,2008.
[181]钱学森.论系统工程[M].湖南科学技术出版社,1982年第一版.
[182]任常兴,吴宗之,刘茂.城市公共场所人群拥挤践踏事故分析[J].中国安全科学学报,2005,15(12)：102-106
[183]沙云飞.人群疏散的微观仿真模型研究[D].清华大学博士学位论文,2009年7月.
[184]史建港.大型活动行人交通特性研究[D].北京工业大学博士论文,2007
[185]隋鹏程,陈宝智,隋旭.安全原理[M],北京：化学工业出版社,2005.
[186]宋卫国,于彦飞,范维澄等.一种考虑摩擦与排斥的人员疏散元胞自动机模型[Jl.中国科学E,2005,35(7)：725-736.
[187]孙超,任彦斌。人群风险分析与控制[J]。现代职业安全,2006：66-67.
[188]唐子来.2010年上海世博会的公共服务设施：经验借鉴和策略建议[J].城市规划会刊,2006,(1)：60-68.
[189]佟瑞鹏.大型社会活动事故风险管理程序与方法[J].自然灾害学报,2007,16(4)：157-163.
[190]王起全,金龙哲,向衍荪.大型公共活动风险控制研究与分析[J].中国安全科学学报,2007,17(1)：141-147.
[191]王炜,石小法.预测型动态交通网络配流模型[J].系统工程学报,2001,16(1)：13-16.
[192]王振,刘茂.离散时间动态网络模型及其在疏散过程中应用的研究[J].中国公共安全(学术版),2006,5：37-40.
[193]王志刚.地下大型商场火灾时期人员疏散计算机模型[J],火灾科学,2001,10(1)：58-62.
[194]魏航,李军,魏洁.时变条件下有宵禁限制的有害物品运输最短路研究[J],管理工程学报,2007,21(3)：79-85.
[195]尾浦恒男(日).城市庆典与市政建设-世博会与大阪[J].东京市政调查会《都市问题》,1980,71(6).
[196]温丽敏,陈宝智.重大事故人员应急疏散模型研究[J].中国安全科学学报,1999,9(6)：69-73.
[197]吴娇蓉，叶建红,陈小鸿.大型活动场馆参观人流服务水平分级研究[J].同济大学学报(自然科学版),2007,35(6)：850-855.
[198]谢振华,孙超,杨琳.大型活动密集人群的风险分析与管理[J].中国公共安全(学术版),2006,12(4)：40-43.
[199]薛谰,等.危机管理-—转型期中国面临的挑战[M].北京：清华大学出版社,2003.
[200]叶亮,崔世华.2010年上海世博会退场引导系统规划研究[C].交通与物流,第六届交通运输领域国际学术会议论文集,2006,417-424.
[201]叶明海,嵇方.大型社会活动人员流动管理模型研究[J].同济大学学报(社会科学版),2006,17(4)：101-106.
[202]叶明海,魏奇.大型会展活动人流聚集和分散复杂系统的分析性框架[J].大连海事大学学报(社会科学版),2006,5(3)：88-92.
[203]叶明海,杨利国.2010世博会潜在人员流动问题分析与对策[J].河北科技大学学报.2006,6(1)：26-30.
[204]于彦飞.人员疏散的多作用力元胞自动机模型研究[D].中国科学技术大学博士学位论文,2008年7月.
[205]约翰·艾伦(澳)等著,王增东,杨磊译.大型活动项目管理[M].机械工业出版社,2002.
[206]张培红,陈宝智,刘丽珍.大型公共建筑物火灾时人员疏散行为规律研究[J],中国安全科学学报,2001,11(2)：23-26.
[207]张好智,高自友.可变车道的交通网络设计优化方法[J].中国管理科学,2007,15(2)：86-90.
[208]张江华,刘治平,朱道立.多源点突发灾害事故应急疏散模型与算法[J].管理科学学报,2009(6),12(3)：111-118
[209]张青松,刘金兰,赵国敏.大型公共场所人群拥挤践踏事故机理初探[J].自然灾害学报,2009,18(6)：81-86.
[210]张涛,张杰,王梦光.不确定车辆数的车辆路径问题模型和混合算法[J].系统工程理论方法应用,2002,11(2)：121-130.
[211]张维迎.博弈论与信息经济学[M].上海人民出版社,1996.
[212]张以琼.会展场馆管理与服务[M].广东经济出版社,2007.