巨灾应对任务的不确定规划模型研究
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摘要
有史以来，人类在生存、生活和发展的同时，必须与各类灾害威胁进行不懈地抗争，尤其是巨灾事件。巨灾事件对人类社会造成巨大的经济损失、大量人员伤亡和大规模设施受损，一直是人类面临的社会性难题。有效的巨灾应对能够减轻损失，减少人员伤亡，保护财产。因此，巨灾应对是政界、学界以及社会各界关注的问题，期望巨灾应对研究工作能够取得实质性进展。
巨灾事件是“小概率大影响”事件，较少发生，一旦爆发即造成灾难性的破坏。巨灾事件极少出现或者不会出现预兆，灾情报告时间和应对决策时间极短；巨灾应对缺乏历史案例参考，预备行动方案策划适应性不足，常规应急决策机制不适用于巨灾应对任务；巨灾应对面临极度不确定性，巨灾应对人员必须在不确定环境下进行应急决策；现有应对资源、保障能力和应对人员不能满足应对需求。因此，巨灾应对组织队伍面临了巨大挑战。
本文的主要研究对象是自然巨灾事件，主要研究内容是巨灾事件爆发后应急响应阶段的应对任务规划问题。
在对国内外现有研究成果梳理和总结的基础上，本文研究了巨灾应对任务分解问题，在巨灾应对的领域任务和基层任务的框架下，借鉴数学领域的不确定理论及不确定规划理论，讨论了巨灾应对任务的不确定属性；采用价值函数度量巨灾应对任务目标；在此基础上，建立了巨灾应对领域任务的不确定规划模型和基层任务的不确定规划模型，开发了不确定双层任务规划模型。
针对巨灾应对任务中应急资源需求缺口大、应急保障能力严重不足的特征，本文采用过载规划模型予以解决。借鉴军事资源规划领域的过载规划研究成果，本文建立了过载规划的数学模型，将其推广到巨灾应对的不确定领域，形成过载规划的不确定规划模型。
首先，建立巨灾应对任务体系。本文借鉴了国内外的灾害应对任务体系，构建了巨灾应对的双层任务体系，包含领域任务层面和基层任务层面。领域任务是针对上层或应对指挥部的应对任务，指上层的、中观的、行业的应对任务，主要内容包括统筹策划任务、资源调配任务和执行协调任务等；基层任务是针对基层应对执行人员的应对任务，指底层的、现场的、一线的应对任务，主要内容包括紧急拯救任务、事态控制任务和民生恢复任务。本文还讨论了各应对任务之间的逻辑关系和时间承接关系。
其次，构造巨灾应对任务的价值函数。研究了巨灾应对任务的不确定属性，根据不确定变量生成方法，建立了巨灾应对任务的不确定变量。针对其不确定特性，构造了巨灾应对任务的价值函数，并以极大价值函数作为任务规划的目标。本文选取社会各界对巨灾应急资源和保障能力的最低期望水平作为巨灾应对任务的价值函数的参照点，依此定义了巨灾应对的“收益”和“损失”；为了消除量纲的影响，定义了巨灾应对任务的达成率，将其代入前景理论的价值函数即得到巨灾应对任务的价值函数。
再次，建立巨灾应对任务规划模型。根据不确定规划理论和过载规划模型的建模机理，建立了巨灾应对任务规划的不确定规划模型。统筹策划规划模型、资源调配规划模型和运输支持任务规划模型，构成了巨灾应对的领域任务规划模型；本文以电力恢复任务规划模型为例，建立了巨灾应对的临时供电任务规划模型、电力枢纽抢修任务规划模型和电力网络抢修任务规划模型，作为巨灾应对的基层任务规划模型的范例。本文采用了过程集成方法，将巨灾应对的领域任务规划模型和基层任务规划模型集成为巨灾应对的双层任务规划模型，还讨论双层任务规划模型的Stachelberg-Nash均衡解的算法。
最后，本文以巨灾事件中大面积电网受损为依赖情景，尝试设计一个巨灾应对任务规划的用例，开展相关试算，以验证本文所提出的巨灾应对不确定规划模型的理论方法和使用过程，证实模型的有效性和实用性。
Since the beginning of history, human shouldn’t only devotes themselves intodevelopment and liberation of the productive forces, the promotion of socia l andhuman, but also must struggle with all kinds of hazards, especially catastrophicevents. Catastrophic events have caused enormous economic losses, mass casualties,infrastructure damage. Recently, catastrophic events have been one of the mainthreats to the human society, has been the social problem of human. Catastrophicresponse could work effectively to reduce the losses caused by catastrophic events,to avoid unnecessary casualties, and to save property of country and people,therefore catastrophic response have been highly concerned by the society politicsand scientists; the whole society hope to make great progress in catastropheresponse.
Catastrophic events have low frequency and litter or no sign, bring about adisastrous impact on society; they are "heavy impacting event with smallprobability". The existing resources and ability cannot meet the demand ofemergency response, conventional emergency response mechanism is not applicableto the catastrophic response task, and this has brought huge challenge ofcatastrophic researchers and response staff. catastrophe response have manyuncertainty, this is one of the biggest difference between catastrophe response taskand general disaster response task; catastrophic events rarely appear or do notappear signs, so the catastrophe response decis ion time is very short, resulting incatastrophic response task decis ion information is not suffic ient.
The main object is the natural disaster catastrophe events, the main researchcontent is to deal with the problem of mission planning in the state of emergencyresponse after catastrophic events outbreak. Based on the review and summary ofthe existing research results, catastrophe task is decomposed into fie ld-levelmissions and basic-level missions. using uncertainty theory and uncertainprogramming theory, uncertainty characters of catastrophe response have beendiscussed; and then value function of catastrophe response missions have beenstudied; on this basis, uncertainty programming model for field-level missionsystem, basic-level mission and bi-level programming model for catastropheresponse missions are built.
Because of the shortage of emergency resources and capabilities, theoversubscribed programming models are built. For reference the oversubscribedplanning problems study in the fie ld of engineering technology, this researchestablishes the mathematical model of oversubscribed programming problems, and extended to uncertain oversubscribed programming model.
At first, it establishes catastrophe response miss sons system in thisdissertation. Based on the catastrophe response mission decomposing practices, thedouble-level catastrophe response missions are constructed in this dissertation,fie ld-level missions system and basic-level missions system. The field-levelmissions are aimed at upper or high response organization(or commanders) to dealwith the tasks; it is macro-layer and professional missions; its main contents includetask over-planning mission, resource allocation mission and execution&coordinated missions; basic-level missions are aimed to deal with the task atbase-layer, refers to deal with tasks in basic-level, at the scene; its main contentinclude emergency rescue missions, disaster control missions and livelihoodrecovery missions. This research also discusses the logic relation and time orderrelationship between each response missions.
The second, value function of catastrophe response missions is constructed.After studying the uncertain attribute of catastrophe response missions, according touncertain statistics method, uncertain variables for catastrophe response missionsare generated. Because of the uncertain characteristics of catastrophe responsemissions, value function of catastrophe response mission is constructed, and thenplanning objectives are to maximizing value function. The reference point of valuefunction is expectations amount of emergency resources and capabilities; ifemergency resources and capabilities supplied are more than reference point, thedifference between them are defined as "incomes" of catastrophe response missions;else defined as "losses". The catastrophic response missions are by value function.
The third, programming model system for catastrophe response missions isestablished. According to the uncertain planning theory and oversubscribedprogramming model established, uncertain programming models for catastropheresponse missions are built, including field-level missions programming models andbasic-level missions programming models. fie ld-level missions programmingmodels are formed by task overall programming models, resource allocationprogramming models and transportation support mission programming models; andbasic-level missions programming models are formed by temporary power supplymissions programming models, power-hub repair missions programming modelsand power-network repair missions programming models.
At fourth, bi-level programming model for catastrophe response missions isestablished. Field-level missions programming models and basic-level missionsprogramming models are integrated into bi-level programming model forcatastrophe response missions, using process model integration method. And then,Stachelberg-Nash equilibrium solution algorithm of bi-level programming model isdiscussed.
Finally, a realistic case by large area power grid damage cause by catastrophicevents in china is designed; and then application of uncertain programming modelfor catastrophe response missions is introduced, the usefulness and practicality isdemonstrated.
巨灾事件是“小概率大影响”事件，较少发生，一旦爆发即造成灾难性的破坏。巨灾事件极少出现或者不会出现预兆，灾情报告时间和应对决策时间极短；巨灾应对缺乏历史案例参考，预备行动方案策划适应性不足，常规应急决策机制不适用于巨灾应对任务；巨灾应对面临极度不确定性，巨灾应对人员必须在不确定环境下进行应急决策；现有应对资源、保障能力和应对人员不能满足应对需求。因此，巨灾应对组织队伍面临了巨大挑战。
本文的主要研究对象是自然巨灾事件，主要研究内容是巨灾事件爆发后应急响应阶段的应对任务规划问题。
在对国内外现有研究成果梳理和总结的基础上，本文研究了巨灾应对任务分解问题，在巨灾应对的领域任务和基层任务的框架下，借鉴数学领域的不确定理论及不确定规划理论，讨论了巨灾应对任务的不确定属性；采用价值函数度量巨灾应对任务目标；在此基础上，建立了巨灾应对领域任务的不确定规划模型和基层任务的不确定规划模型，开发了不确定双层任务规划模型。
针对巨灾应对任务中应急资源需求缺口大、应急保障能力严重不足的特征，本文采用过载规划模型予以解决。借鉴军事资源规划领域的过载规划研究成果，本文建立了过载规划的数学模型，将其推广到巨灾应对的不确定领域，形成过载规划的不确定规划模型。
首先，建立巨灾应对任务体系。本文借鉴了国内外的灾害应对任务体系，构建了巨灾应对的双层任务体系，包含领域任务层面和基层任务层面。领域任务是针对上层或应对指挥部的应对任务，指上层的、中观的、行业的应对任务，主要内容包括统筹策划任务、资源调配任务和执行协调任务等；基层任务是针对基层应对执行人员的应对任务，指底层的、现场的、一线的应对任务，主要内容包括紧急拯救任务、事态控制任务和民生恢复任务。本文还讨论了各应对任务之间的逻辑关系和时间承接关系。
其次，构造巨灾应对任务的价值函数。研究了巨灾应对任务的不确定属性，根据不确定变量生成方法，建立了巨灾应对任务的不确定变量。针对其不确定特性，构造了巨灾应对任务的价值函数，并以极大价值函数作为任务规划的目标。本文选取社会各界对巨灾应急资源和保障能力的最低期望水平作为巨灾应对任务的价值函数的参照点，依此定义了巨灾应对的“收益”和“损失”；为了消除量纲的影响，定义了巨灾应对任务的达成率，将其代入前景理论的价值函数即得到巨灾应对任务的价值函数。
再次，建立巨灾应对任务规划模型。根据不确定规划理论和过载规划模型的建模机理，建立了巨灾应对任务规划的不确定规划模型。统筹策划规划模型、资源调配规划模型和运输支持任务规划模型，构成了巨灾应对的领域任务规划模型；本文以电力恢复任务规划模型为例，建立了巨灾应对的临时供电任务规划模型、电力枢纽抢修任务规划模型和电力网络抢修任务规划模型，作为巨灾应对的基层任务规划模型的范例。本文采用了过程集成方法，将巨灾应对的领域任务规划模型和基层任务规划模型集成为巨灾应对的双层任务规划模型，还讨论双层任务规划模型的Stachelberg-Nash均衡解的算法。
最后，本文以巨灾事件中大面积电网受损为依赖情景，尝试设计一个巨灾应对任务规划的用例，开展相关试算，以验证本文所提出的巨灾应对不确定规划模型的理论方法和使用过程，证实模型的有效性和实用性。
Since the beginning of history, human shouldn’t only devotes themselves intodevelopment and liberation of the productive forces, the promotion of socia l andhuman, but also must struggle with all kinds of hazards, especially catastrophicevents. Catastrophic events have caused enormous economic losses, mass casualties,infrastructure damage. Recently, catastrophic events have been one of the mainthreats to the human society, has been the social problem of human. Catastrophicresponse could work effectively to reduce the losses caused by catastrophic events,to avoid unnecessary casualties, and to save property of country and people,therefore catastrophic response have been highly concerned by the society politicsand scientists; the whole society hope to make great progress in catastropheresponse.
Catastrophic events have low frequency and litter or no sign, bring about adisastrous impact on society; they are "heavy impacting event with smallprobability". The existing resources and ability cannot meet the demand ofemergency response, conventional emergency response mechanism is not applicableto the catastrophic response task, and this has brought huge challenge ofcatastrophic researchers and response staff. catastrophe response have manyuncertainty, this is one of the biggest difference between catastrophe response taskand general disaster response task; catastrophic events rarely appear or do notappear signs, so the catastrophe response decis ion time is very short, resulting incatastrophic response task decis ion information is not suffic ient.
The main object is the natural disaster catastrophe events, the main researchcontent is to deal with the problem of mission planning in the state of emergencyresponse after catastrophic events outbreak. Based on the review and summary ofthe existing research results, catastrophe task is decomposed into fie ld-levelmissions and basic-level missions. using uncertainty theory and uncertainprogramming theory, uncertainty characters of catastrophe response have beendiscussed; and then value function of catastrophe response missions have beenstudied; on this basis, uncertainty programming model for field-level missionsystem, basic-level mission and bi-level programming model for catastropheresponse missions are built.
Because of the shortage of emergency resources and capabilities, theoversubscribed programming models are built. For reference the oversubscribedplanning problems study in the fie ld of engineering technology, this researchestablishes the mathematical model of oversubscribed programming problems, and extended to uncertain oversubscribed programming model.
At first, it establishes catastrophe response miss sons system in thisdissertation. Based on the catastrophe response mission decomposing practices, thedouble-level catastrophe response missions are constructed in this dissertation,fie ld-level missions system and basic-level missions system. The field-levelmissions are aimed at upper or high response organization(or commanders) to dealwith the tasks; it is macro-layer and professional missions; its main contents includetask over-planning mission, resource allocation mission and execution&coordinated missions; basic-level missions are aimed to deal with the task atbase-layer, refers to deal with tasks in basic-level, at the scene; its main contentinclude emergency rescue missions, disaster control missions and livelihoodrecovery missions. This research also discusses the logic relation and time orderrelationship between each response missions.
The second, value function of catastrophe response missions is constructed.After studying the uncertain attribute of catastrophe response missions, according touncertain statistics method, uncertain variables for catastrophe response missionsare generated. Because of the uncertain characteristics of catastrophe responsemissions, value function of catastrophe response mission is constructed, and thenplanning objectives are to maximizing value function. The reference point of valuefunction is expectations amount of emergency resources and capabilities; ifemergency resources and capabilities supplied are more than reference point, thedifference between them are defined as "incomes" of catastrophe response missions;else defined as "losses". The catastrophic response missions are by value function.
The third, programming model system for catastrophe response missions isestablished. According to the uncertain planning theory and oversubscribedprogramming model established, uncertain programming models for catastropheresponse missions are built, including field-level missions programming models andbasic-level missions programming models. fie ld-level missions programmingmodels are formed by task overall programming models, resource allocationprogramming models and transportation support mission programming models; andbasic-level missions programming models are formed by temporary power supplymissions programming models, power-hub repair missions programming modelsand power-network repair missions programming models.
At fourth, bi-level programming model for catastrophe response missions isestablished. Field-level missions programming models and basic-level missionsprogramming models are integrated into bi-level programming model forcatastrophe response missions, using process model integration method. And then,Stachelberg-Nash equilibrium solution algorithm of bi-level programming model isdiscussed.
Finally, a realistic case by large area power grid damage cause by catastrophicevents in china is designed; and then application of uncertain programming modelfor catastrophe response missions is introduced, the usefulness and practicality isdemonstrated.
引文
1Dirk Helbing， Christian Kühnert． Assessing interaction networks withapplications to catastrophe dynamics and disaster management [J]．Physica A:Statistical Mechanics and its Applications．2003，328(3-4):584-606
2Stefan Hochrainer，Reinhard Mechler．Natural disaster risk in Asian megacities: Acase for risk pooling?[J]．Cities．2011，28(1):53-61
3张卫星，史培军，周洪建．巨灾定义与划分标准研究———基于近年来全球典型灾害案例的分析[J]．灾害学．2013，28(1):15-22
4ongzhong Jia，Fernando Ordó ez，Maged M. Dessouky．Solution approaches forfacility location of medical supplies for large-scale emergencies[J]．Computers&Industrial Engineering．2007，52(2):257-276
5Michael R. Weeks．Organizing for disaster: Lessons from the military[J]．BusinessHorizons．2007，50:479–489
6Lubos Buzna，Karsten Peters，Dirk Helbing．Modelling the dynamics of disasterspreading in networks [J]． Physica A: Statistical Mechanics and itsApplications．2006，363(1):132-140
7韩智勇，翁文国，张维，杨列勋．重大研究计划―非常规突发事件应急管理研究‖的科学背景目标与组织管理[J]．中国科学基金学科进展与展望．2009(4):15-220
8王飞跃，邱晓刚，曾大军，曹志冬，樊宗臣．基于平行系统的非常规突发事件计算实验平台研究[J]．复杂系统与复杂性科学．2010，7(4):1-10
9韩传峰，王兴广，孔静静．非常规突发事件应急决策系统动态作用机理[J]．战略与对策．2009，23(8):50-53
10王旭坪，李小龙，梁阿密．SOA非常规突发事件资源协调决策系统研究[J]．情报杂志．2010，29(6):164-169
11佘廉，沈照磊．非常规突发事件下基于SIR模型的群体行为分析．情报杂志．2011，30(5):14-18
12Yang-Che Wu，San-Lin Chung．Catastrophe risk management with counterpartyrisk using alternative instruments[J]． Insurance: Mathematics andEconomics．2010，47(2):234-245
13Wikimedia Foundation．Catastrophe[EB/OL]．http://en.wikipedia.org．2013
14百度．巨灾事件[EB/OL]．http://baike.baidu.com．2013
15A. D. Akkaya，M. S. Yücemen．Stochastic modeling of earthquake occurrencesand estimation of seismic hazard: a random field approach [J]．ProbabilisticEngineering Mechanics．2002，17(1):1-13
16韩传峰，王兴广，孔静静．非常规突发事件应急决策系统动态作用机理[J]．软科学．2008，23(8):50-53
17张一文，齐佳音，方滨兴，李欲晓．非常规突发事件网络舆情指标体系建立初探——概念界定与基本维度[J]．北京邮电大学学报(社会科学版)．2010，12(4):6-14
18Seth D. Guikema．Natural disaster risk analysis for critical infrastructure systems:An approach based on statistical learning theory [J]．Reliability Engineering&System Safety．2009，94(4):855-860
19薛澜，朱琴．危机管理的国际借鉴：以美国突发公共卫生事件应对体系为例[J]．中国行政管理．2003，8:51-56
20John R. Harrald．Agility and Discipline: Critical Success Factors for DisasterResponse [J]．The ANNALS of the American Academy of Political and SocialScience．2006:256-272
21Lucien G. Canton．Emergency management: concepts and strategies for effectiveprograms [J]．Wiley，2007:11-113
22Kovel Jacob Paul．Planning construction for disaster response[D]．GeorgiaInstitute of Technology．1996:23-101
23Marie Flanigan． Response to crisis and disaster management through theintegration of technology into a virtual consolidated operationscenter[D]．Colorado Technical University．1998:42-98
24J.D. Goltz，Los Angeles University of California．Initial Behavioral Response toa Rapid Onset Disaster: A Social Psychological Study of Three CaliforniaEarthquakes [J]．University of California, Los Angeles，2006
25D.M. Smith． A Study of Command and Control of Multi-agency DisasterResponse Operations[D]．University of Phoenix．2010
26Poggione Sarah，Gawronski Vincent T.，Hoberman Gabriela，Gabriela，OlsonRichard Stuart．Public Response to Disaster Response: Applying the―5C+A‖Framework to El Salvador2001and Peru2007[M]．Blackwell Publishing Ltd，2012
27Jessica Anne Jensen． Emergency Management Policy: Predicting NationalIncident Management System (Nims) Implementation Behavior[D]． NorthDakota State University of Agriculture and Applied Science．2011:51-133
28周广亮．应急资源配置与调度文献综述与思考[J]．预测．2011，30(3):76-80
29耿泽飞，胡飞虎，陈慧敏，孙林岩．多灾害点应急资源调度研究与实现[J]．计算机应用与软件．2010，27(2):63-66
30李进，张江华，朱道立．灾害链中多资源应急调度模型与算法[J]．系统工程理论与实践．2011，31(3):488-495
31杨继君，吴启迪，程艳，许维胜，韩传峰．面向非常规突发事件的应急资源合作博弈调度[J]．系统工程．2008，26(9):21-25
32张杰，王志勇，许维胜，杨继君．面向突发事件的应急资源调度模型的构建和求解[J]．计算机工程与应用．2011，47(31):220-223
33李梅霞，车海涛．应急资源调度模型及算法[J]．运筹与管理．2011，20(3):72-76
34张海龙，李雄飞，王仁彪．启发式遗传算法求解应急资源调度[J]．吉林大学学报（工学版）．2010，4(3):758-762
35Linet zdamar，Onur Demir．A hierarchical clustering and routing procedure forlarge scale disaster relief logistics planning[J]．Transportation Research Part E:Logistics and Transportation Review．2012，48(3):591-602
36L. Hick John， Rubinson Lewis， T. O'Laughlin Daniel， J. ChristopherFarmer．Clinical review: Allocating ventilators during large-scale disasters–problems, planning, and process [J]．Critical Care．2007，11(3):217-217
37Jiuh-Biing Sheu．Dynamic relief-demand management for emergency logisticsoperations under large-scale disasters[J]． Transportation Research Part E:Logistics and Transportation Review．2010，46(1):1-17
38Kenneth P. Moritsugu，Thomas P. Reutershan．The national disaster medicalsystem: A concept in large-scale emergency medical care[J]． Annals ofEmergency Medicine．1986，15(12):1496-1498
39Seiichi Kobayashi，Masakazu Hanagama，Shinsuke Yamanda，Yamanda，Satoh,Hikari，Tokuda, Shinsaku，Kobayashi, Masakazu，Ueda, Shinsaku，Suzuk i,Satoshi，Yanai, Masaru．The impact of a large-scale natural disaster on patientswith chronic obstructive pulmonary disease: The aftermath of the2011GreatEast Japan Earthquake[J]．Respiratory Investigation．2012，1(1):1-7
40A. Meissner．Emergency Management in Australia, New Zealand and Europe-The2006EMANZE Survey[J]． Intelligence and Security Informatics,IEEE．2007:368-368
41The Emergency Management Accreditation Program． A Framework forAssessing Regional Preparedness[EB/OL]．http://www.fema.gov．2006
42Robert D. Stenner，Jennifer L. Kirk，Smokey Stanton，P. Shebell，Deborah S.Schwartz．National Incident Management System (NIMS) Standards Rev iewPanel Workshop Summary Report[J]． Pacific Northwest NationalLaboratory．2006
43徐富海．国际巨灾风险管理和志愿者服务[J]．中国减灾．2009，6(1):42-44
44DHS． Target Capabilities List-A companion to the National PreparednessGuideliness[EB/OL]．http://www.fema.gov．2007
45U.S. Department of Homeland Security． Emergency Support Functions[EB/OL]．http://www.fema.gov．2008
46U.S. Department of Homeland Security． National Infrastructure ProtectionPlan[EB/OL]．http://www.fema.gov．2009
47Homeland Security of USA． National Incident ManagementSystem[EB/OL]．http://www.fema.gov/．2004
48Homeland Security of USA． National PreparednessGuidelines[EB/OL]．http://www.fema.gov/．2007
49Homeland Security of USA． National Incident Management System(NIMS)What’s New[EB/OL]．http://www.fema.gov/．2008
50Homeland Security of USA． National Incident ManagementSystem[EB/OL]．http://www.fema.gov/．2008
51Homeland Security of USA．Privacy Impact Assessment for the TSA OperationsCenter Incident Management System[EB/OL]．http://www.fema.gov/．2008
52Homeland Security of USA． national emergency communicationsplan[EB/OL]．http://www.fema.gov/．2008
53Homeland Security of USA．DHS' Progress in Federal Incident ManagementPlanning[EB/OL]．http://www.fema.gov/．2010
54李湖生．国内外应急准备规划体系比较研究[J]．中国安全生产科学技术．2011，7(10):5-10
55UK Cabinet Office．Emergency Response and Recovery,Non-statutory guidanceto complement[EB/OL]．http://www.cabinetoffice.gov.uk/．2005
56郭跃．澳大利亚灾害管理的特征及其启示[J]．重庆师范大学学报(自然科学版)．2005，22(4):53-57
57Emergency management Australia． Emergency management in Australiaconcepts and princ iples Mamual number[EB/OL]．http://www.ema.gov.au．2004
58Emergency management Australia．National action plan for the attraction,support and retention of emergency management volunteersEndorsed[EB/OL]．http://www.ema.gov.au．2009
59Emergency management Australia．Natural Disasters in Australia--Reformingmitigation, relief and recoveryarrangements[EB/OL]．http://www.ema.gov.au．2002
60庄丽，高惠瑛，谭黎明．中日美地震应急管理模式比较[J]．世界地震工程．2009，25(3):97-101
61姚国章．日本突发公共事件应急管理体系解析[J]．电子政务．2007，7(1):58-67
62中华人民共和国中央人民政府门户网站．应急管理[EB/OL]．http://www.gov.cn/yjgl/tfsj.htm
63赵阿兴，马宗晋．自然灾害损失评估指标体系的研究[J]．自然灾害学报．1993，2(3):1-6
64李志强，徐敬海，李晓丽．亚洲巨灾划分研究[J]．地震地质．2012，34(4):792-804
65杨静，陈建明，赵红．应急管理中的突发事件分级分类研究[J]．管理评论．2005，17(4):37-41
66马庆国，王小毅．非常规突发事件中影响当事人状态的要素分析与数理描述[J]．管理工程学报．2009，23(3):126-130
67杨继君，吴启迪，程艳，许维胜．面向非常规突发事件的应对方案序贯决策[J]．同济大学学报(自然科学版)．2010，38(4):619-624
68姚杰，计雷，池宏．突发事件应急管理中的动态博弈分析[J]．管理评论．2005，17(3):46-50
69王旭坪，傅克俊，胡祥培．应急物流系统及其快速反应机制研究[J]．企业战略．2005，6:127-131
70David J. Mendon a，William A. Wallace．A Cognitive Model of Improvisation inEmergency Management[J]． IEEE Transactions on systems, man, andcybernetics—part a: systems and humans．2007，37(4):547-561
71Zhi-Hua Hu． Relief demand forecasting in emergency logistics based ontolerance model [J]． IEEE Third International Joint Conference onComputational Science and Optimization(CSO)．2010:1-5
72陈森，姜江，陈英武，沈永平．未定路网结构情况下应急屋子车辆配送问题模型与应用[J]．系统工程理论与实践．2011，31(5):907-913
73Peng Yongjun，Zou Zili，Guo Xi，Yang Min，Chen Jinming．Research on TheEmergency Resource Allocation and Scheduling Model Under UnconventionalSocial Emergency[J]．IEEE2010Second International Workshop on EducationTechnology and Computer Science．2010，1:559-562
74晏湘涛，曾华锋，石海明．非常规突发事件中军民一体的指挥体系研究[J]．国防科技．2009，30(2):52-56
75杨文国，黄钧，郭田德．大规模突发事件中伤员救助的救护车分配优化模型[J]．系统工程理论与实践．2010，30(7):1218-1224
76刘宝碇，赵宝瑞，王刚．不确定规划及应用[M]．清华大学出版社，2007:1-278
77A. Charnes，W. W. Cooper．Chance-constrained programming [J]．ManagementScience．1959，6(1):73-79
78Baoding Liu．Uncertain Programmin[M]．Wiley，1999:1-247
79Baoding Liu． Dependent-chance programming: A class of stochasticoptimization[J]．Computers& Mathematics with Applications．1997，34(12):89-104
80L.A. Zadeh．fuzzy set as a basis for a theory of possibility[J]．Fuzzy Sets andSystems．1978，3-28(1)
81Didier Dubois，Henri Prade．Possibility Theory: An Approach to ComputerizedProcessing of Uncertainty[J]．New York: Plenum，1988:11-101
82Didier Dubois，Henri Prade．Fuzzy numbers: an overview [J]．Analysis of FuzzyInformation．1994，2:3-39
83Arnold Kaufmann．Introduction to the Theory of Fuzzy Subsets [M]．AcademicPr，1975
84L.A.Zadeh． The Concept of a Linguistic Variable and its Application toApproximate Reasoning[J]．Information Sciences．1975，8:199-249
85Steven Nahmias．Fuzzy variables[J]．Fuzzy Sets and Systems．1978，1(2):97-110
86Baoding Liu，Yian-Kui Liu．Expected value of fuzzy variable and fuzzy expectedvalue models [J]．IEEE Transactions on Fuzzy Systems．2002，10(4):445-450
87Baoding Liu，Kakuzo Iwamura．A note on chance constrained programming withfuzzy coefficients [J]．Fuzzy Sets and Systems．1998，100(1–3):229-233
88Baoding Liu． Minimax chance constrained programming models for fuzzydecision systems[J]．Information Sciences．1998，112(1–4):25-38
89Baoding Liu，Kakuzo Iwamura．Chance constrained programming with fuzzyparameters [J]．Fuzzy Sets and Systems．1998，94(2):227-237
90Baoding Liu．Dependent-chance programming in fuzzy environments[J]．FuzzySets and Systems．2000，109(1):97-106
91Zdzis law Pawlak． Rough sets[J]． International Journal of Information andComputer Sciences．1982，11(5):341--356
92Boading Liu． Theory and Practice of Uncertain Programming[M]．Physica-Verlag Heidelberg，2003:15-300
93Peng Lv，Peng Chang．Rough Programming and Its Application to ProductionPlanning [J]． ICRMEM '08. International Conference on Risk Management&Engineering Management．2008:136-140
94Bastian Cock，Rinnooy Kan，Alexander H. G.．The stochastic vehicle routingproblem revisited[J]． European Journal of Operational Research．1992，56(3):407-412
95Dimitris J. Bertsimas，David Simchi-Levi．A new generation of vehicle routingresearch: Robust algorithms, addressing uncertainty [J]． OperationalResearch．1996，44(2):286-304
96Moshe Dror，Gilbert Laporte，Pierre Trudeau．Vehic le routing with stochasticdemands: Properties and solution frameworks[J]．Transportation Science．1989，23(3):166-176
97Michel Gendreau，Gilbert Laporte，RenéSéguin．Stochastic vehicle routing[J]．European Journal of Operational Research．1996，88(1):3-12
98Gilbert Laporte，Fran ois Louveaux，Hélène Mercure．The vehicle routingproblem with stochastic travel times[J]． Transportation Science．1992，26:161-170
99Baoding Liu，K. K. Lai．Stochastic programming models for vehicle routingproblems[J]．Asian Information Science Life．2002，1(1):13-28
100CDJ Waters． Vehile-scheduling problems with uncertainty and omittedcustomers[J]． Journal of the Operational Research Society．1989，40:1099-1108
101Ruiqing Zhao，Baoding Liu．Stochastic programming models for generalredundancy optimization problems[J]．IEEE Transactions on Reliability．2003，52(2):181-191
102Jian Zhou， Baoding Liu． New stochastic models for capacitatedlocation-allocation problem．Computers& Industrial Engineering．2003，45(1):111-125
103J Zhong，Baoding Liu．The critical path problem: Stochastic models and hybridintelligent algorithm[R]．Technical Report．2003
104Jing Peng，Baoding Liu．Stochastic goal programming models for parallelmachine scheduling problems[J]．Asian Information Science Life．2002，1(3):257-266
105Ruiqing Zhao，Baoding Liu．Standby redundancy optimization problems withfuzzy lifetimes[J]． Computers& Industrial Engineering．2005，49(2):318-338
106K. K. Lai，Baoding Liu，Jing Peng．Vehicle routing problem with fuzzy traveltimes and its nenetic algorithm[R]．Technical Report．2003
107J. Zhong， Baoding Liu． Fuzzy critical path problem: Stochasticmodels[R]．Technical Report．2003
108Jing Peng， Baoding Liu．Parallel machine scheduling model with fuzzyprocessing times [R]．Technical Report．2003
109J. Zhou，Baoding Liu．Modelling capacitated location-allocation problem withfuzzy demands．Technical Report．2003
110Baoding Liu，K. Iwamura．Topological optimization models for communicationnetwork with multiple reliability goals[J]．Computers& Mathematicswith Applications．2000，39(7–8):59-69
111Baoding Liu． Uncertainty Theory (Fourth Edition)[EB/OL]．http://orsc.edu.cn．2011
112Jing Peng， Baoding Liu． Paralle l machine scheduling model with fuzzyprocessing times[R]．Technical Report．2003
113J. Zhou，Baoding Liu．Modelling capacitated location-allocation problem withfuzzy demands[R]．Technical Report．2003
114Baoding Liu． Uncertainty Theory (Seconde Edition)[M]．Springer-Verlag,Berlin，2007:1-141
115Baoding Liu，Kai Yao．Uncertain Multilevel Programming: Algorithm andApplications[EB/OL]．www.orsc.edu.cn．2012
116Stephen F. Smith，Dhiraj K. Pathak．Balancing antagonistic time and resourceutilization constraints in over-subscribed scheduling problems[J]．Proceedings of the Eighth Conference on Artificial Intelligence forApplications．1992:113-119
117Philippe Baptiste，Claude Pape，Laurent Peridy．Global Constraints for PartialCSPs: A Case-Study of Resource and Due Date Constraints [J]．SpringerBerlin Heidelberg，1998:8
118J.C. Pemberton． Towards scheduling over-constrained remote sensingsatellites[J]．Proceedings of the2d International Workshop on Planning andScheduling for Space．2000:84-89
119郭玉华，李军，赵珂，王钧，景宁．多星联合任务规划的迭代修复求解技术[J]．系统工程与电子技术．2009，31(8):1958-1962
120Jeremy Frank，Ari Jonsson，Robert Morris，David E. Smith．Planning andScheduling for Fleets of Earth ObservingSatellites．http://ti.arc.nasa.gov．2001
121Sarah E. Burrowbridge．Oprimal allocation of satellite network resources [J]．InMaster's Thesis. Virginia Polytechnic Institute and StateUniversity．1999:31-81
122S. Chien，G. Rabideau，R. Knight，Knight，R. Sherwood，B. Engel-hardt，D. Mutz， T. Estlin， B. Smith，F. Fisher， T. Barrett， G. Stebbins， D.Tran． ASPEN-Automating Space Mission Operations using AutomatedPlanning and Scheduling [J]．International Conference on Space Operations(SpaceOps2000)．2000:1-53
123Mark D. Johnston，Glenn E. Mille．Spike: Intelligent scheduling of hubblespace telescope observations [J]．Intelligent Scheduling．1994:391-422
124Gregg Rabideau，Steve Chien，Jason Willis，Tobias Mann．Using iterative repairto automate planning and scheduling of shuttle payloadoperations[J]．Proceedings of the sixteenth national conference on Artificia lintelligence and the eleventh Innovative applications of artificial intelligenceconference innovative applications of artific ial intelligence．1999:813-820
125Gilbert Syswerda．Schedule optimization using genetic algorithms[J]．VanNostrand Reinhold，1991:253-311
126Laura V. Barbulescu． Oversubscribed Scheduling Problems[EB/OL]．http://www-math.ucdenver.edu．2002
127Danie l Kahneman，Amos Tversky．Prospect theory: Ananalysis of decis ionunder risk[J]．Econometrica．1979，47:263-291
128Amos Tversky，Daniel Kahneman．advance in prospect theory: cumulativerepresentation of uncertainty[J]．Journal of Risk and Uncertainty．1992，5:297-323
129Wakker Peter P.，Zank Horst．A simple preference foundation of cumulativeprospect theory with power utility[J]．European Economic Review．2002，46(7):1253-1271
130Prelec Drazen．The Probability Weighting Function[J]．Econmometrica．1998，66(3):497-527
131Marc Oliver Rieger， Thuy Bui． Too Risk-Averse for ProspectTheory?[J]．Modern Economy．2011，2:691-700
132Colin F. Camerer，Teck-Hua Ho．Violations of the betweenness axiom andnonlinearity in probability [J]．Journal of Risk and Uncertainty．1994，8(2):167-196
133George Wu， Richard Gon． Curvature of the Probability WeightingFunction[J]．Management Science．1996，42(12):1676-1690
134曾建敏．实验检验累积前景理论[J]．暨南大学学报(自然科学版)．2007，28(1):44-65
135王敬，张莹，李延喜．期望理论及价值函数的实证研究[J]．大连理工大学学报(社会科学版)．2006，27(2):37-41
136王颜新．非常规突发事件情境重构模型研究[D]．哈尔滨工业大学．2011:1-95
137Department of Homeland U.S.．Catastrophic Incident Supplement to theNational Response Plan[EB/OL]．http://www.fema.gov/．2005
138U.S. Department of Homeland Security． National Response Framework[EB/OL]．http://www.fema.gov/．2008
139Emergency Management Australia． Emergency Planning[EB/OL]．www.ema.gov.au/．2004
140Emergency Management Australia．Emergency Management Concepts andPrinciples [EB/OL]．www.ema.gov.au/．2004
141姚国章．典型国家突发公共事件应急管理体系及其借鉴[J]．南京审计学院学报．2006，3(2):5-10
142陈成文，蒋勇，黄娟．应急管理：国外模式及其启示[J]．甘肃社会科学．2010，5(1):201-206
143钟开斌．―一案三制"：中国应急管理体系建设的基本框架[J]．南京社会科学．2009，11(1):77-83
144姜平．中国特色应急管理体系的构建和完善[J]．理论探讨．2011，2(1):138-142
145田卫东，赵利．面向多层级出救点的应急物资调度模型研究[J]．计算机应用研究．2011，28(11):4045-4048
146汪传旭，邓先明．模糊环境下多出救点应急救援车辆路径与物资运输优化研究[J]．系统管理学报．2011，20(3):269-275
147柴秀荣，王儒．多出救点、多物资应急调度算法研究[J]．计算机工程与应用．2010，46(6):224-226
148Dantizig G， Ranser J． The truck dispatching problem [J]． ManagementScience．1959，6:80~91
149Jian Zhou， Baoding Liu． New stochastic models for capacitatedlocation-allocation problem[J]． Computers& IndustrialEngineering．2003，45(1):111-125
150Yuhong Sheng．A Transportation Model with Uncertain Cost, Supplies andDemands[EB/OL]．http://orsc.edu.cn．2010
151Meng Wang， Xingfang Zhang． Machine Scheduling Problem Based onUncertainty Theory[J]．Proceedings of the First International Conference onUncertainty Theory．2010:131-135
152Fengjiao Zhang， Xingfang Zhang． Vehicle Routing Problem Based onUncertainty Theory[J]．Proceedings of the First International Conference onUncertainty Theory．2010:136-141
153王绍仁，马祖军．震害紧急响应阶段应急物流系统中的LRP[J]．系统工程理论与实践．2011，31(8):1497-1507
154万凤娇，张庆年，周业旺．危险废物定位一运输路线安排问题模型和算法研究[J]．武汉理工大学学报(交通科学与工程版)．2010，34(1):80-83
155张潜，高立群，胡祥培．集成化物流中的定位-运输路线安排问题（LRP）优化算法评述[J]．东北大学学报（自然科学版）．2003，24(1):31-34
156汪寿阳，赵秋红，夏国平．集成物流管理系统中定位-运输路线安排问题的研究[J]．管理科学学报．2000，3(2):69-75
157崔广彬．一体化物流网络布局中的定位-运输路线安排问题研究[D]．哈尔滨工业大学．2006:1-101
158王树禾．图论（第二版）[M]．科学出版社，2011:32-41
159王树禾．几类多投递员中国邮路问题[J]．中国科学技术大学学报．1995，25(4):454-460
160Department of Homeland Security， Department of Homeland Security，Department of Interior，Interior，Department of Commerce，Department ofDefense， Department of Transportation，National Aeronautics and SpaceAdministration，Federal Communications Commission．Catastrophic inc identsearch and rescue addendum to the National Search and RescueManual[EB/OL]．www.uscg.mil/nsarc．2008
161中国地震应急搜救中心．中国地震应急搜救中心[EB/OL]．http://www.nerss.cn/
162史培军．灾害研究的理论与实践[J]．南京大学学报(自然科学版)．1991，11:37-42
163史培军．三论灾害系统研究的理论与实践[J]．自然灾害学报．2002，11(3):01-09
164史培军．四论灾害系统研究的理论与实践[J]．自然灾害学报．2005，14(6):01-07
165史培军．五论灾害系统研究的理论与实践[J]．自然灾害学报．2009，18(5):01-09
166史培军．再论灾害研究的理论与实践[J]．自然灾害学报．1996，5(4):6-17
167Baoding Liu．Uncertainty Theory: A Branch of Mathematics for ModelingHuman Uncertainty [J]．Springer-Verlag, Berlin，2010:1-152
168Xiaosheng Wang，Zixiong Peng．Method of moments for estimating uncertaintydistributions[EB/OL]．http://orsc.edu.cn．2010
169Amos Tversky，Daniel Kahneman．Rational choice and the framming ofdecision[J]．Journal of Business．1986，59(4):251-278
170Gustave Choquet．Theory of capacities [J]．Annales de l'institut Fourier．1954，5:131-295
171Han Bleichrodt，Ulrich Schmidt，Horst Zank．Additive Utility in ProspectTheory [J]．Management Science．2009，55(5):863–873
172陈希．电网应急平台研究与建设[M]．中国电力出版社，2011
173G. Syswerda．Schedule Optimization Using Genetic Algorithms． In LawrenceDavis, editor, Handbook of Genetic Algorithms, chapter21.Van NostrandReinhold, NY．1991
174Michael R. Garey，David S. Johnson．Computers and intractability: a guide tothe theory of np-completeness [J]．W. H. Freeman，1979:187-285
175岳超源．决策理论与方法[M]．科学出版社，2003:206-214
176于锐，曹介南，朱培．车辆运输路径规划问题研究[J]．计算机技术与发展．2011，21(1):5-8
177Billy E. Gillett， Leland R. Miller． A Heuristic Algorithm for theVehicle-Dispatch Problem [J]．Operations Research．1974，22(2):340-349
178Michel Gendreau，Alain Hertz，Gilbert Laporte．A Tabu Search Heuristic forthe Vehicle Routing Problem [J]． Management Science．1994，40(10):1276-1290
179张潜，高立群，胡祥培．集成化物流中的定位运输路线安排问题(LRP)优化算法评述．东北大学学报(自然科学版)．2003，24(1):31-34
180张潜，高立群，刘雪梅，胡祥培．定位-运输路线安排问题的两阶段启发式算法[J]．控制与决策．2004，19(7):773-777
181蔡树彬，明仲，李师贤，刘显明．基于本体的模型集成[J]．电子学报．2009，37(4):713-719
182谢勇，王红卫．模型集成及其优化策略[J]．计算机集成制造系统．2005，11(1):58-62
183唐锡晋．模型集成[J]．系统工程学报．2001，16(5):322-329
184Jerome Bracken，James T. McGill．Mathematical Programs with OptimizationProblems in the Constraints [J]．Operations Research．1973，21(1):37-44
185W. Candler， R.D. Norton． Multi-level programming [J]．World Bank，1977:23-51
186王广民，万仲平，王先甲．二(双)层规划综述[J]．数学进展．2007，26(5):513-529
187Omar Ben-Ayed，Charles E. Blair．computational difficulties of bilever linearprogramming [J]．Operations Research．1990，38(3):556-560
188Jonathan F. Bard．practical bilevel optimization:algorithms and applications(1stedition)[M]．Springer，1999
189Pierre Hansen，Brigitte Jaumard，Gilles Savard．New branch-and-bound rulesfor linear bilevel programming [J]．SIAM Journal on Scientific and StatisticalComputing．1992，13(5):1194-1217
190L. Vicente，G. Savard，J. Júdice．Descent approaches for quadratic bilevelprogramming [J]．Journal of Optimization Theory and Applications．1994，81(2):379-399
2Stefan Hochrainer，Reinhard Mechler．Natural disaster risk in Asian megacities: Acase for risk pooling?[J]．Cities．2011，28(1):53-61
3张卫星，史培军，周洪建．巨灾定义与划分标准研究———基于近年来全球典型灾害案例的分析[J]．灾害学．2013，28(1):15-22
4ongzhong Jia，Fernando Ordó ez，Maged M. Dessouky．Solution approaches forfacility location of medical supplies for large-scale emergencies[J]．Computers&Industrial Engineering．2007，52(2):257-276
5Michael R. Weeks．Organizing for disaster: Lessons from the military[J]．BusinessHorizons．2007，50:479–489
6Lubos Buzna，Karsten Peters，Dirk Helbing．Modelling the dynamics of disasterspreading in networks [J]． Physica A: Statistical Mechanics and itsApplications．2006，363(1):132-140
7韩智勇，翁文国，张维，杨列勋．重大研究计划―非常规突发事件应急管理研究‖的科学背景目标与组织管理[J]．中国科学基金学科进展与展望．2009(4):15-220
8王飞跃，邱晓刚，曾大军，曹志冬，樊宗臣．基于平行系统的非常规突发事件计算实验平台研究[J]．复杂系统与复杂性科学．2010，7(4):1-10
9韩传峰，王兴广，孔静静．非常规突发事件应急决策系统动态作用机理[J]．战略与对策．2009，23(8):50-53
10王旭坪，李小龙，梁阿密．SOA非常规突发事件资源协调决策系统研究[J]．情报杂志．2010，29(6):164-169
11佘廉，沈照磊．非常规突发事件下基于SIR模型的群体行为分析．情报杂志．2011，30(5):14-18
12Yang-Che Wu，San-Lin Chung．Catastrophe risk management with counterpartyrisk using alternative instruments[J]． Insurance: Mathematics andEconomics．2010，47(2):234-245
13Wikimedia Foundation．Catastrophe[EB/OL]．http://en.wikipedia.org．2013
14百度．巨灾事件[EB/OL]．http://baike.baidu.com．2013
15A. D. Akkaya，M. S. Yücemen．Stochastic modeling of earthquake occurrencesand estimation of seismic hazard: a random field approach [J]．ProbabilisticEngineering Mechanics．2002，17(1):1-13
16韩传峰，王兴广，孔静静．非常规突发事件应急决策系统动态作用机理[J]．软科学．2008，23(8):50-53
17张一文，齐佳音，方滨兴，李欲晓．非常规突发事件网络舆情指标体系建立初探——概念界定与基本维度[J]．北京邮电大学学报(社会科学版)．2010，12(4):6-14
18Seth D. Guikema．Natural disaster risk analysis for critical infrastructure systems:An approach based on statistical learning theory [J]．Reliability Engineering&System Safety．2009，94(4):855-860
19薛澜，朱琴．危机管理的国际借鉴：以美国突发公共卫生事件应对体系为例[J]．中国行政管理．2003，8:51-56
20John R. Harrald．Agility and Discipline: Critical Success Factors for DisasterResponse [J]．The ANNALS of the American Academy of Political and SocialScience．2006:256-272
21Lucien G. Canton．Emergency management: concepts and strategies for effectiveprograms [J]．Wiley，2007:11-113
22Kovel Jacob Paul．Planning construction for disaster response[D]．GeorgiaInstitute of Technology．1996:23-101
23Marie Flanigan． Response to crisis and disaster management through theintegration of technology into a virtual consolidated operationscenter[D]．Colorado Technical University．1998:42-98
24J.D. Goltz，Los Angeles University of California．Initial Behavioral Response toa Rapid Onset Disaster: A Social Psychological Study of Three CaliforniaEarthquakes [J]．University of California, Los Angeles，2006
25D.M. Smith． A Study of Command and Control of Multi-agency DisasterResponse Operations[D]．University of Phoenix．2010
26Poggione Sarah，Gawronski Vincent T.，Hoberman Gabriela，Gabriela，OlsonRichard Stuart．Public Response to Disaster Response: Applying the―5C+A‖Framework to El Salvador2001and Peru2007[M]．Blackwell Publishing Ltd，2012
27Jessica Anne Jensen． Emergency Management Policy: Predicting NationalIncident Management System (Nims) Implementation Behavior[D]． NorthDakota State University of Agriculture and Applied Science．2011:51-133
28周广亮．应急资源配置与调度文献综述与思考[J]．预测．2011，30(3):76-80
29耿泽飞，胡飞虎，陈慧敏，孙林岩．多灾害点应急资源调度研究与实现[J]．计算机应用与软件．2010，27(2):63-66
30李进，张江华，朱道立．灾害链中多资源应急调度模型与算法[J]．系统工程理论与实践．2011，31(3):488-495
31杨继君，吴启迪，程艳，许维胜，韩传峰．面向非常规突发事件的应急资源合作博弈调度[J]．系统工程．2008，26(9):21-25
32张杰，王志勇，许维胜，杨继君．面向突发事件的应急资源调度模型的构建和求解[J]．计算机工程与应用．2011，47(31):220-223
33李梅霞，车海涛．应急资源调度模型及算法[J]．运筹与管理．2011，20(3):72-76
34张海龙，李雄飞，王仁彪．启发式遗传算法求解应急资源调度[J]．吉林大学学报（工学版）．2010，4(3):758-762
35Linet zdamar，Onur Demir．A hierarchical clustering and routing procedure forlarge scale disaster relief logistics planning[J]．Transportation Research Part E:Logistics and Transportation Review．2012，48(3):591-602
36L. Hick John， Rubinson Lewis， T. O'Laughlin Daniel， J. ChristopherFarmer．Clinical review: Allocating ventilators during large-scale disasters–problems, planning, and process [J]．Critical Care．2007，11(3):217-217
37Jiuh-Biing Sheu．Dynamic relief-demand management for emergency logisticsoperations under large-scale disasters[J]． Transportation Research Part E:Logistics and Transportation Review．2010，46(1):1-17
38Kenneth P. Moritsugu，Thomas P. Reutershan．The national disaster medicalsystem: A concept in large-scale emergency medical care[J]． Annals ofEmergency Medicine．1986，15(12):1496-1498
39Seiichi Kobayashi，Masakazu Hanagama，Shinsuke Yamanda，Yamanda，Satoh,Hikari，Tokuda, Shinsaku，Kobayashi, Masakazu，Ueda, Shinsaku，Suzuk i,Satoshi，Yanai, Masaru．The impact of a large-scale natural disaster on patientswith chronic obstructive pulmonary disease: The aftermath of the2011GreatEast Japan Earthquake[J]．Respiratory Investigation．2012，1(1):1-7
40A. Meissner．Emergency Management in Australia, New Zealand and Europe-The2006EMANZE Survey[J]． Intelligence and Security Informatics,IEEE．2007:368-368
41The Emergency Management Accreditation Program． A Framework forAssessing Regional Preparedness[EB/OL]．http://www.fema.gov．2006
42Robert D. Stenner，Jennifer L. Kirk，Smokey Stanton，P. Shebell，Deborah S.Schwartz．National Incident Management System (NIMS) Standards Rev iewPanel Workshop Summary Report[J]． Pacific Northwest NationalLaboratory．2006
43徐富海．国际巨灾风险管理和志愿者服务[J]．中国减灾．2009，6(1):42-44
44DHS． Target Capabilities List-A companion to the National PreparednessGuideliness[EB/OL]．http://www.fema.gov．2007
45U.S. Department of Homeland Security． Emergency Support Functions[EB/OL]．http://www.fema.gov．2008
46U.S. Department of Homeland Security． National Infrastructure ProtectionPlan[EB/OL]．http://www.fema.gov．2009
47Homeland Security of USA． National Incident ManagementSystem[EB/OL]．http://www.fema.gov/．2004
48Homeland Security of USA． National PreparednessGuidelines[EB/OL]．http://www.fema.gov/．2007
49Homeland Security of USA． National Incident Management System(NIMS)What’s New[EB/OL]．http://www.fema.gov/．2008
50Homeland Security of USA． National Incident ManagementSystem[EB/OL]．http://www.fema.gov/．2008
51Homeland Security of USA．Privacy Impact Assessment for the TSA OperationsCenter Incident Management System[EB/OL]．http://www.fema.gov/．2008
52Homeland Security of USA． national emergency communicationsplan[EB/OL]．http://www.fema.gov/．2008
53Homeland Security of USA．DHS' Progress in Federal Incident ManagementPlanning[EB/OL]．http://www.fema.gov/．2010
54李湖生．国内外应急准备规划体系比较研究[J]．中国安全生产科学技术．2011，7(10):5-10
55UK Cabinet Office．Emergency Response and Recovery,Non-statutory guidanceto complement[EB/OL]．http://www.cabinetoffice.gov.uk/．2005
56郭跃．澳大利亚灾害管理的特征及其启示[J]．重庆师范大学学报(自然科学版)．2005，22(4):53-57
57Emergency management Australia． Emergency management in Australiaconcepts and princ iples Mamual number[EB/OL]．http://www.ema.gov.au．2004
58Emergency management Australia．National action plan for the attraction,support and retention of emergency management volunteersEndorsed[EB/OL]．http://www.ema.gov.au．2009
59Emergency management Australia．Natural Disasters in Australia--Reformingmitigation, relief and recoveryarrangements[EB/OL]．http://www.ema.gov.au．2002
60庄丽，高惠瑛，谭黎明．中日美地震应急管理模式比较[J]．世界地震工程．2009，25(3):97-101
61姚国章．日本突发公共事件应急管理体系解析[J]．电子政务．2007，7(1):58-67
62中华人民共和国中央人民政府门户网站．应急管理[EB/OL]．http://www.gov.cn/yjgl/tfsj.htm
63赵阿兴，马宗晋．自然灾害损失评估指标体系的研究[J]．自然灾害学报．1993，2(3):1-6
64李志强，徐敬海，李晓丽．亚洲巨灾划分研究[J]．地震地质．2012，34(4):792-804
65杨静，陈建明，赵红．应急管理中的突发事件分级分类研究[J]．管理评论．2005，17(4):37-41
66马庆国，王小毅．非常规突发事件中影响当事人状态的要素分析与数理描述[J]．管理工程学报．2009，23(3):126-130
67杨继君，吴启迪，程艳，许维胜．面向非常规突发事件的应对方案序贯决策[J]．同济大学学报(自然科学版)．2010，38(4):619-624
68姚杰，计雷，池宏．突发事件应急管理中的动态博弈分析[J]．管理评论．2005，17(3):46-50
69王旭坪，傅克俊，胡祥培．应急物流系统及其快速反应机制研究[J]．企业战略．2005，6:127-131
70David J. Mendon a，William A. Wallace．A Cognitive Model of Improvisation inEmergency Management[J]． IEEE Transactions on systems, man, andcybernetics—part a: systems and humans．2007，37(4):547-561
71Zhi-Hua Hu． Relief demand forecasting in emergency logistics based ontolerance model [J]． IEEE Third International Joint Conference onComputational Science and Optimization(CSO)．2010:1-5
72陈森，姜江，陈英武，沈永平．未定路网结构情况下应急屋子车辆配送问题模型与应用[J]．系统工程理论与实践．2011，31(5):907-913
73Peng Yongjun，Zou Zili，Guo Xi，Yang Min，Chen Jinming．Research on TheEmergency Resource Allocation and Scheduling Model Under UnconventionalSocial Emergency[J]．IEEE2010Second International Workshop on EducationTechnology and Computer Science．2010，1:559-562
74晏湘涛，曾华锋，石海明．非常规突发事件中军民一体的指挥体系研究[J]．国防科技．2009，30(2):52-56
75杨文国，黄钧，郭田德．大规模突发事件中伤员救助的救护车分配优化模型[J]．系统工程理论与实践．2010，30(7):1218-1224
76刘宝碇，赵宝瑞，王刚．不确定规划及应用[M]．清华大学出版社，2007:1-278
77A. Charnes，W. W. Cooper．Chance-constrained programming [J]．ManagementScience．1959，6(1):73-79
78Baoding Liu．Uncertain Programmin[M]．Wiley，1999:1-247
79Baoding Liu． Dependent-chance programming: A class of stochasticoptimization[J]．Computers& Mathematics with Applications．1997，34(12):89-104
80L.A. Zadeh．fuzzy set as a basis for a theory of possibility[J]．Fuzzy Sets andSystems．1978，3-28(1)
81Didier Dubois，Henri Prade．Possibility Theory: An Approach to ComputerizedProcessing of Uncertainty[J]．New York: Plenum，1988:11-101
82Didier Dubois，Henri Prade．Fuzzy numbers: an overview [J]．Analysis of FuzzyInformation．1994，2:3-39
83Arnold Kaufmann．Introduction to the Theory of Fuzzy Subsets [M]．AcademicPr，1975
84L.A.Zadeh． The Concept of a Linguistic Variable and its Application toApproximate Reasoning[J]．Information Sciences．1975，8:199-249
85Steven Nahmias．Fuzzy variables[J]．Fuzzy Sets and Systems．1978，1(2):97-110
86Baoding Liu，Yian-Kui Liu．Expected value of fuzzy variable and fuzzy expectedvalue models [J]．IEEE Transactions on Fuzzy Systems．2002，10(4):445-450
87Baoding Liu，Kakuzo Iwamura．A note on chance constrained programming withfuzzy coefficients [J]．Fuzzy Sets and Systems．1998，100(1–3):229-233
88Baoding Liu． Minimax chance constrained programming models for fuzzydecision systems[J]．Information Sciences．1998，112(1–4):25-38
89Baoding Liu，Kakuzo Iwamura．Chance constrained programming with fuzzyparameters [J]．Fuzzy Sets and Systems．1998，94(2):227-237
90Baoding Liu．Dependent-chance programming in fuzzy environments[J]．FuzzySets and Systems．2000，109(1):97-106
91Zdzis law Pawlak． Rough sets[J]． International Journal of Information andComputer Sciences．1982，11(5):341--356
92Boading Liu． Theory and Practice of Uncertain Programming[M]．Physica-Verlag Heidelberg，2003:15-300
93Peng Lv，Peng Chang．Rough Programming and Its Application to ProductionPlanning [J]． ICRMEM '08. International Conference on Risk Management&Engineering Management．2008:136-140
94Bastian Cock，Rinnooy Kan，Alexander H. G.．The stochastic vehicle routingproblem revisited[J]． European Journal of Operational Research．1992，56(3):407-412
95Dimitris J. Bertsimas，David Simchi-Levi．A new generation of vehicle routingresearch: Robust algorithms, addressing uncertainty [J]． OperationalResearch．1996，44(2):286-304
96Moshe Dror，Gilbert Laporte，Pierre Trudeau．Vehic le routing with stochasticdemands: Properties and solution frameworks[J]．Transportation Science．1989，23(3):166-176
97Michel Gendreau，Gilbert Laporte，RenéSéguin．Stochastic vehicle routing[J]．European Journal of Operational Research．1996，88(1):3-12
98Gilbert Laporte，Fran ois Louveaux，Hélène Mercure．The vehicle routingproblem with stochastic travel times[J]． Transportation Science．1992，26:161-170
99Baoding Liu，K. K. Lai．Stochastic programming models for vehicle routingproblems[J]．Asian Information Science Life．2002，1(1):13-28
100CDJ Waters． Vehile-scheduling problems with uncertainty and omittedcustomers[J]． Journal of the Operational Research Society．1989，40:1099-1108
101Ruiqing Zhao，Baoding Liu．Stochastic programming models for generalredundancy optimization problems[J]．IEEE Transactions on Reliability．2003，52(2):181-191
102Jian Zhou， Baoding Liu． New stochastic models for capacitatedlocation-allocation problem．Computers& Industrial Engineering．2003，45(1):111-125
103J Zhong，Baoding Liu．The critical path problem: Stochastic models and hybridintelligent algorithm[R]．Technical Report．2003
104Jing Peng，Baoding Liu．Stochastic goal programming models for parallelmachine scheduling problems[J]．Asian Information Science Life．2002，1(3):257-266
105Ruiqing Zhao，Baoding Liu．Standby redundancy optimization problems withfuzzy lifetimes[J]． Computers& Industrial Engineering．2005，49(2):318-338
106K. K. Lai，Baoding Liu，Jing Peng．Vehicle routing problem with fuzzy traveltimes and its nenetic algorithm[R]．Technical Report．2003
107J. Zhong， Baoding Liu． Fuzzy critical path problem: Stochasticmodels[R]．Technical Report．2003
108Jing Peng， Baoding Liu．Parallel machine scheduling model with fuzzyprocessing times [R]．Technical Report．2003
109J. Zhou，Baoding Liu．Modelling capacitated location-allocation problem withfuzzy demands．Technical Report．2003
110Baoding Liu，K. Iwamura．Topological optimization models for communicationnetwork with multiple reliability goals[J]．Computers& Mathematicswith Applications．2000，39(7–8):59-69
111Baoding Liu． Uncertainty Theory (Fourth Edition)[EB/OL]．http://orsc.edu.cn．2011
112Jing Peng， Baoding Liu． Paralle l machine scheduling model with fuzzyprocessing times[R]．Technical Report．2003
113J. Zhou，Baoding Liu．Modelling capacitated location-allocation problem withfuzzy demands[R]．Technical Report．2003
114Baoding Liu． Uncertainty Theory (Seconde Edition)[M]．Springer-Verlag,Berlin，2007:1-141
115Baoding Liu，Kai Yao．Uncertain Multilevel Programming: Algorithm andApplications[EB/OL]．www.orsc.edu.cn．2012
116Stephen F. Smith，Dhiraj K. Pathak．Balancing antagonistic time and resourceutilization constraints in over-subscribed scheduling problems[J]．Proceedings of the Eighth Conference on Artificial Intelligence forApplications．1992:113-119
117Philippe Baptiste，Claude Pape，Laurent Peridy．Global Constraints for PartialCSPs: A Case-Study of Resource and Due Date Constraints [J]．SpringerBerlin Heidelberg，1998:8
118J.C. Pemberton． Towards scheduling over-constrained remote sensingsatellites[J]．Proceedings of the2d International Workshop on Planning andScheduling for Space．2000:84-89
119郭玉华，李军，赵珂，王钧，景宁．多星联合任务规划的迭代修复求解技术[J]．系统工程与电子技术．2009，31(8):1958-1962
120Jeremy Frank，Ari Jonsson，Robert Morris，David E. Smith．Planning andScheduling for Fleets of Earth ObservingSatellites．http://ti.arc.nasa.gov．2001
121Sarah E. Burrowbridge．Oprimal allocation of satellite network resources [J]．InMaster's Thesis. Virginia Polytechnic Institute and StateUniversity．1999:31-81
122S. Chien，G. Rabideau，R. Knight，Knight，R. Sherwood，B. Engel-hardt，D. Mutz， T. Estlin， B. Smith，F. Fisher， T. Barrett， G. Stebbins， D.Tran． ASPEN-Automating Space Mission Operations using AutomatedPlanning and Scheduling [J]．International Conference on Space Operations(SpaceOps2000)．2000:1-53
123Mark D. Johnston，Glenn E. Mille．Spike: Intelligent scheduling of hubblespace telescope observations [J]．Intelligent Scheduling．1994:391-422
124Gregg Rabideau，Steve Chien，Jason Willis，Tobias Mann．Using iterative repairto automate planning and scheduling of shuttle payloadoperations[J]．Proceedings of the sixteenth national conference on Artificia lintelligence and the eleventh Innovative applications of artificial intelligenceconference innovative applications of artific ial intelligence．1999:813-820
125Gilbert Syswerda．Schedule optimization using genetic algorithms[J]．VanNostrand Reinhold，1991:253-311
126Laura V. Barbulescu． Oversubscribed Scheduling Problems[EB/OL]．http://www-math.ucdenver.edu．2002
127Danie l Kahneman，Amos Tversky．Prospect theory: Ananalysis of decis ionunder risk[J]．Econometrica．1979，47:263-291
128Amos Tversky，Daniel Kahneman．advance in prospect theory: cumulativerepresentation of uncertainty[J]．Journal of Risk and Uncertainty．1992，5:297-323
129Wakker Peter P.，Zank Horst．A simple preference foundation of cumulativeprospect theory with power utility[J]．European Economic Review．2002，46(7):1253-1271
130Prelec Drazen．The Probability Weighting Function[J]．Econmometrica．1998，66(3):497-527
131Marc Oliver Rieger， Thuy Bui． Too Risk-Averse for ProspectTheory?[J]．Modern Economy．2011，2:691-700
132Colin F. Camerer，Teck-Hua Ho．Violations of the betweenness axiom andnonlinearity in probability [J]．Journal of Risk and Uncertainty．1994，8(2):167-196
133George Wu， Richard Gon． Curvature of the Probability WeightingFunction[J]．Management Science．1996，42(12):1676-1690
134曾建敏．实验检验累积前景理论[J]．暨南大学学报(自然科学版)．2007，28(1):44-65
135王敬，张莹，李延喜．期望理论及价值函数的实证研究[J]．大连理工大学学报(社会科学版)．2006，27(2):37-41
136王颜新．非常规突发事件情境重构模型研究[D]．哈尔滨工业大学．2011:1-95
137Department of Homeland U.S.．Catastrophic Incident Supplement to theNational Response Plan[EB/OL]．http://www.fema.gov/．2005
138U.S. Department of Homeland Security． National Response Framework[EB/OL]．http://www.fema.gov/．2008
139Emergency Management Australia． Emergency Planning[EB/OL]．www.ema.gov.au/．2004
140Emergency Management Australia．Emergency Management Concepts andPrinciples [EB/OL]．www.ema.gov.au/．2004
141姚国章．典型国家突发公共事件应急管理体系及其借鉴[J]．南京审计学院学报．2006，3(2):5-10
142陈成文，蒋勇，黄娟．应急管理：国外模式及其启示[J]．甘肃社会科学．2010，5(1):201-206
143钟开斌．―一案三制"：中国应急管理体系建设的基本框架[J]．南京社会科学．2009，11(1):77-83
144姜平．中国特色应急管理体系的构建和完善[J]．理论探讨．2011，2(1):138-142
145田卫东，赵利．面向多层级出救点的应急物资调度模型研究[J]．计算机应用研究．2011，28(11):4045-4048
146汪传旭，邓先明．模糊环境下多出救点应急救援车辆路径与物资运输优化研究[J]．系统管理学报．2011，20(3):269-275
147柴秀荣，王儒．多出救点、多物资应急调度算法研究[J]．计算机工程与应用．2010，46(6):224-226
148Dantizig G， Ranser J． The truck dispatching problem [J]． ManagementScience．1959，6:80~91
149Jian Zhou， Baoding Liu． New stochastic models for capacitatedlocation-allocation problem[J]． Computers& IndustrialEngineering．2003，45(1):111-125
150Yuhong Sheng．A Transportation Model with Uncertain Cost, Supplies andDemands[EB/OL]．http://orsc.edu.cn．2010
151Meng Wang， Xingfang Zhang． Machine Scheduling Problem Based onUncertainty Theory[J]．Proceedings of the First International Conference onUncertainty Theory．2010:131-135
152Fengjiao Zhang， Xingfang Zhang． Vehicle Routing Problem Based onUncertainty Theory[J]．Proceedings of the First International Conference onUncertainty Theory．2010:136-141
153王绍仁，马祖军．震害紧急响应阶段应急物流系统中的LRP[J]．系统工程理论与实践．2011，31(8):1497-1507
154万凤娇，张庆年，周业旺．危险废物定位一运输路线安排问题模型和算法研究[J]．武汉理工大学学报(交通科学与工程版)．2010，34(1):80-83
155张潜，高立群，胡祥培．集成化物流中的定位-运输路线安排问题（LRP）优化算法评述[J]．东北大学学报（自然科学版）．2003，24(1):31-34
156汪寿阳，赵秋红，夏国平．集成物流管理系统中定位-运输路线安排问题的研究[J]．管理科学学报．2000，3(2):69-75
157崔广彬．一体化物流网络布局中的定位-运输路线安排问题研究[D]．哈尔滨工业大学．2006:1-101
158王树禾．图论（第二版）[M]．科学出版社，2011:32-41
159王树禾．几类多投递员中国邮路问题[J]．中国科学技术大学学报．1995，25(4):454-460
160Department of Homeland Security， Department of Homeland Security，Department of Interior，Interior，Department of Commerce，Department ofDefense， Department of Transportation，National Aeronautics and SpaceAdministration，Federal Communications Commission．Catastrophic inc identsearch and rescue addendum to the National Search and RescueManual[EB/OL]．www.uscg.mil/nsarc．2008
161中国地震应急搜救中心．中国地震应急搜救中心[EB/OL]．http://www.nerss.cn/
162史培军．灾害研究的理论与实践[J]．南京大学学报(自然科学版)．1991，11:37-42
163史培军．三论灾害系统研究的理论与实践[J]．自然灾害学报．2002，11(3):01-09
164史培军．四论灾害系统研究的理论与实践[J]．自然灾害学报．2005，14(6):01-07
165史培军．五论灾害系统研究的理论与实践[J]．自然灾害学报．2009，18(5):01-09
166史培军．再论灾害研究的理论与实践[J]．自然灾害学报．1996，5(4):6-17
167Baoding Liu．Uncertainty Theory: A Branch of Mathematics for ModelingHuman Uncertainty [J]．Springer-Verlag, Berlin，2010:1-152
168Xiaosheng Wang，Zixiong Peng．Method of moments for estimating uncertaintydistributions[EB/OL]．http://orsc.edu.cn．2010
169Amos Tversky，Daniel Kahneman．Rational choice and the framming ofdecision[J]．Journal of Business．1986，59(4):251-278
170Gustave Choquet．Theory of capacities [J]．Annales de l'institut Fourier．1954，5:131-295
171Han Bleichrodt，Ulrich Schmidt，Horst Zank．Additive Utility in ProspectTheory [J]．Management Science．2009，55(5):863–873
172陈希．电网应急平台研究与建设[M]．中国电力出版社，2011
173G. Syswerda．Schedule Optimization Using Genetic Algorithms． In LawrenceDavis, editor, Handbook of Genetic Algorithms, chapter21.Van NostrandReinhold, NY．1991
174Michael R. Garey，David S. Johnson．Computers and intractability: a guide tothe theory of np-completeness [J]．W. H. Freeman，1979:187-285
175岳超源．决策理论与方法[M]．科学出版社，2003:206-214
176于锐，曹介南，朱培．车辆运输路径规划问题研究[J]．计算机技术与发展．2011，21(1):5-8
177Billy E. Gillett， Leland R. Miller． A Heuristic Algorithm for theVehicle-Dispatch Problem [J]．Operations Research．1974，22(2):340-349
178Michel Gendreau，Alain Hertz，Gilbert Laporte．A Tabu Search Heuristic forthe Vehicle Routing Problem [J]． Management Science．1994，40(10):1276-1290
179张潜，高立群，胡祥培．集成化物流中的定位运输路线安排问题(LRP)优化算法评述．东北大学学报(自然科学版)．2003，24(1):31-34
180张潜，高立群，刘雪梅，胡祥培．定位-运输路线安排问题的两阶段启发式算法[J]．控制与决策．2004，19(7):773-777
181蔡树彬，明仲，李师贤，刘显明．基于本体的模型集成[J]．电子学报．2009，37(4):713-719
182谢勇，王红卫．模型集成及其优化策略[J]．计算机集成制造系统．2005，11(1):58-62
183唐锡晋．模型集成[J]．系统工程学报．2001，16(5):322-329
184Jerome Bracken，James T. McGill．Mathematical Programs with OptimizationProblems in the Constraints [J]．Operations Research．1973，21(1):37-44
185W. Candler， R.D. Norton． Multi-level programming [J]．World Bank，1977:23-51
186王广民，万仲平，王先甲．二(双)层规划综述[J]．数学进展．2007，26(5):513-529
187Omar Ben-Ayed，Charles E. Blair．computational difficulties of bilever linearprogramming [J]．Operations Research．1990，38(3):556-560
188Jonathan F. Bard．practical bilevel optimization:algorithms and applications(1stedition)[M]．Springer，1999
189Pierre Hansen，Brigitte Jaumard，Gilles Savard．New branch-and-bound rulesfor linear bilevel programming [J]．SIAM Journal on Scientific and StatisticalComputing．1992，13(5):1194-1217
190L. Vicente，G. Savard，J. Júdice．Descent approaches for quadratic bilevelprogramming [J]．Journal of Optimization Theory and Applications．1994，81(2):379-399
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