突发性灾害事件下应急物资分配决策优化过程研究
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摘要
突发性灾害事件在中国及全球范围内频发,对社会经济造成了极大破坏,应急管理及相关决策支持系统的研究和开发已经成为应对日益严峻的突发性灾害事件的迫切需要。由于应急物资分配是突发性灾害事件救灾的关键,作为应急管理和应急物流管理的重要分支,应急物资分配决策的研究已经成为国内外学术界研究的热点问题。
首先,在分析当前国内外关于应急决策和应急物资管理的研究现状的基础上,提出了能有效保障突发事件应急救援的应急物资需求的基于全过程的优化分配决策思路；然后深入研究应急物资管理及应急物资分配决策的科学内涵,剖析应急物资分配决策的特点和决策过程；最后对需求预测、分配决策和方案评价整个决策过程进行系统研究,为应急决策机构和人员提供了应急物资分配的预测模型、分配决策模型、评价模型以及相关算法。论文的研究内容与创新点主要包括：
(1)应急物资分配决策特性分析。研究应急物资分配决策系统的内涵以及构成要素,从系统构成要素的角度研究应急物资分配决策的特点,设计了应急物资分配决策过程。认为应急物资分配决策是一个动态的决策过程,应急物资分配决策系统是一个由多个阶段组成的循环系统。在每一个决策周期内,应该包含完整的信息收集、分配决策、方案评价、方案实施四个阶段。
(2)应急物资需求预测模型研究。总结应急物流情景下与一般物流情景下的物资需求预测方法的不同之处,提出在突发性灾害事件发生后的黄金救援时间内,对应急物资需求预测应该采用间接预测的方法,即先预测伤亡人口数量再预测应急物资需求量。设计了需求预测的四个步骤,包括定性分析伤亡人口相关因素、定量分析伤亡人口相关因素、BP神经网络模型预测伤亡人口数量和应急物资需求预测。针对预测过程中的四个步骤提出系列模型,并以大型地震中应急物资需求预测为例对各个步骤进行了阐述。
(3)应急物资最优分配模型研究。分两个阶段进行。第一阶段是拥有二级节点网络的分配模型的构建。针对救援物资在短时间内不能全部满足灾害事件产生的应急需求,提出不完全扑灭灾情的策略,构建了以受灾点为局中人,以分配方案为策略集的完全信息非合作博弈模型。为了解决节点和分配量过多导致策略集过大的问题,采用分步规划法,即第一步以响应时间最短为目标对受灾点独立进行初始分配,第二步针对发生冲突的受灾点建立博弈模型。通过构建适应度函数,提出用粒子群优化算法求模型的纳什均衡解。用一个数值算例来验证模型的有效性,结果表明该模型在解决供需不平衡的应急物资分配问题时,可以兼顾救援中的效率与公平,反映出较好的救灾效果；第二阶段是拥有三级节点网络的分配模型构建。综合考虑我国应急管理实践、应急响应时间限制,以及应急物资分配中的公平要求,在三级应急物资运输网络的基础上,建立了以系统损失最小为目标的应急物资分配决策模型。针对模型的整数非线性规划的特点提出了改进粒子群(PSO)算法,通过在不同维度上确定不同学习对象,加强了粒子的空间搜索能力。数值算例验证了模型和算法的有效性。
(4)应急物资分配方案评价模型研究。首先分析了对应急物资分配方案评价应遵循的原则,分析公平与效率之间的辩证关系,认为对应急物资分配方案的评价应强调公平原则；然后分析公平、公平分配的含义,以及应急物资公平分配的内涵；最后建立了计算简便、容易理解且性能较好的应急物资分配决策方案公平测度模型,该模型考虑了受灾点的不同需求量要求以及对物资的不同需求紧迫程度,并应用模型对三级节点算例的分配方案进行评价。
对上述问题的研究,可以为突发性灾害事件下的应急物资分配决策提供科学依据,从而提高应急物流及应急物资保障系统的运作效率,减少由于灾害造成的人员伤亡和财产损失。
Since the sudden disaster events happened frequently in China and worldwide caused great damage to the socio-economic, the research on emergency management and the development of decision support systems have become an urgent need to deal with the increasingly severe sudden disaster events. Because the distribution of emergency supplies is the key problem for the relief to unexpected disaster events, emergency supplies distribution decision, as an important branch of the emergency management and emergency logistics management, has become a hot issue in academic research at home and abroad.
Firstly, the paper proposed the research thought of emergency supplies optimization distribution decision based on the whole process of the decision in order to provide effective protection for the demand of the emergency supplies based on the analysis of the current research status on emergency decision-making and emergency supplies management in domestic and foreign. Secondly, the paper explained the connotation of emergency supplies distribution decision, analyzed its characteristics and the decision-making process. Lastly and importantly, the paper provided emergency supplies prediction model, emergency supplies distribution models and evaluation model for the decision scheme and their algorithms to the emergency decision-making bodies and staff. The main research content and innovation in this paper are as follows.
(1)Analysis of the characteristics of the emergency supplies distribution decision. Through studying the connotation and the elements of emergency supplies distribution decision system, the characteristics of emergency supplies distribution decision was analyzed from the angle of system elements and the emergency supplies distribution decision-making process was designed. It was believed that emergency supplies distribution decision was a dynamic decision-making process, and the emergency supplies distribution decision-making system was a circulatory system composed of multiple stages. Every decision cycle should include complete four stages, namely, information collection, distribution decision, program evaluation, plan implementation.
(2)Research on the emergency supplies demand forecast model. Based on the different points of supplies demand forecast methods between the emergency logistics situation and general logistics situation, a indirect prediction method was provided to forecast the emergency supplies demand in a gold rescue time after sudden disaster events occurred, namely to forecast the population casualties first, then the emergency supplies demand. Four steps was designed to predict the demand, including qualitative analysis and quantitative analysis of factors associated with injuries population, a BP neural network model to predict the casualty population and the prediction of the emergency supplies demand. According to the four steps, specific models were put forward and described as an example of the emergency supplies demand forecast in a large earthquake.
(3)Research on the optimal emergency supplies distribution model including two stages. The first stage is the building of the model based on two-layer node networks and the game theory. A strategy of so-called incomplete put-out was proposed when relief supplies could not meet the emergency needs within a short time. A non-cooperative game model based on complete information was presented, in which the affected points corresponded to the players, and the distribution schemes to the strategies. A phased planning approach was used to reduce the number of the strategies caused by too many nodes and distribution supplies. The approach can realize the initial distribution of aiming at shorting the response time, and the second planning of establishing a game model for the conflicting nodes after the initial distribution. The Nash equilibrium of the model was found by using particle swarm optimization algorithm through constructing a fitness function. A numerical analysis was conducted to test the effectiveness of the model. The results show that the model does well in distributing the emergency supplies efficiently and fairly when imbalance between supply and demand occurs, and reaches a better rescue effect. The second stage is the building of the distribution model of emergency supplies with three-layer node networks existing in the practice of emergency management. The model aims at minimizing the system losses and meets the constraints of emergency response time and fairness constraint. A modified particle swarm optimization algorithm was proposed for the integer nonlinear programming, the spatial search abilities of the particles were improved by determining different learning objects for different dimensions of the particles. Finally a numerical example was conducted to test the effectiveness of the model and the algorithm.
(4)Research on the evaluation model of emergency supplies distribution scheme. Firstly, the principle on the emergency supplies distribution scheme evaluation should follow was analyzed; it is believed that the principle of fairness should be emphasized when evaluating the emergency supplies distribution scheme after the analysis of the dialectical relationship between impartiality and efficiency; Secondly, the meaning of the fair and the equitable distribution, the connotation of the emergency supplies fair distribution was analyzed; Finally, a simple, easy to understand fair measure model was proposed which took into account the different requirements and urgency degree for supplies. The model was applied to the evaluation of the distribution scheme in the example with three-layer node networks.
The above research can provide scientific basis for emergency supplies distribution decision-making, thereby enhance the operational efficiency of the emergency logistics and emergency supplies support system, and reduce casualties and property losses caused by disasters.
首先,在分析当前国内外关于应急决策和应急物资管理的研究现状的基础上,提出了能有效保障突发事件应急救援的应急物资需求的基于全过程的优化分配决策思路；然后深入研究应急物资管理及应急物资分配决策的科学内涵,剖析应急物资分配决策的特点和决策过程；最后对需求预测、分配决策和方案评价整个决策过程进行系统研究,为应急决策机构和人员提供了应急物资分配的预测模型、分配决策模型、评价模型以及相关算法。论文的研究内容与创新点主要包括：
(1)应急物资分配决策特性分析。研究应急物资分配决策系统的内涵以及构成要素,从系统构成要素的角度研究应急物资分配决策的特点,设计了应急物资分配决策过程。认为应急物资分配决策是一个动态的决策过程,应急物资分配决策系统是一个由多个阶段组成的循环系统。在每一个决策周期内,应该包含完整的信息收集、分配决策、方案评价、方案实施四个阶段。
(2)应急物资需求预测模型研究。总结应急物流情景下与一般物流情景下的物资需求预测方法的不同之处,提出在突发性灾害事件发生后的黄金救援时间内,对应急物资需求预测应该采用间接预测的方法,即先预测伤亡人口数量再预测应急物资需求量。设计了需求预测的四个步骤,包括定性分析伤亡人口相关因素、定量分析伤亡人口相关因素、BP神经网络模型预测伤亡人口数量和应急物资需求预测。针对预测过程中的四个步骤提出系列模型,并以大型地震中应急物资需求预测为例对各个步骤进行了阐述。
(3)应急物资最优分配模型研究。分两个阶段进行。第一阶段是拥有二级节点网络的分配模型的构建。针对救援物资在短时间内不能全部满足灾害事件产生的应急需求,提出不完全扑灭灾情的策略,构建了以受灾点为局中人,以分配方案为策略集的完全信息非合作博弈模型。为了解决节点和分配量过多导致策略集过大的问题,采用分步规划法,即第一步以响应时间最短为目标对受灾点独立进行初始分配,第二步针对发生冲突的受灾点建立博弈模型。通过构建适应度函数,提出用粒子群优化算法求模型的纳什均衡解。用一个数值算例来验证模型的有效性,结果表明该模型在解决供需不平衡的应急物资分配问题时,可以兼顾救援中的效率与公平,反映出较好的救灾效果；第二阶段是拥有三级节点网络的分配模型构建。综合考虑我国应急管理实践、应急响应时间限制,以及应急物资分配中的公平要求,在三级应急物资运输网络的基础上,建立了以系统损失最小为目标的应急物资分配决策模型。针对模型的整数非线性规划的特点提出了改进粒子群(PSO)算法,通过在不同维度上确定不同学习对象,加强了粒子的空间搜索能力。数值算例验证了模型和算法的有效性。
(4)应急物资分配方案评价模型研究。首先分析了对应急物资分配方案评价应遵循的原则,分析公平与效率之间的辩证关系,认为对应急物资分配方案的评价应强调公平原则；然后分析公平、公平分配的含义,以及应急物资公平分配的内涵；最后建立了计算简便、容易理解且性能较好的应急物资分配决策方案公平测度模型,该模型考虑了受灾点的不同需求量要求以及对物资的不同需求紧迫程度,并应用模型对三级节点算例的分配方案进行评价。
对上述问题的研究,可以为突发性灾害事件下的应急物资分配决策提供科学依据,从而提高应急物流及应急物资保障系统的运作效率,减少由于灾害造成的人员伤亡和财产损失。
Since the sudden disaster events happened frequently in China and worldwide caused great damage to the socio-economic, the research on emergency management and the development of decision support systems have become an urgent need to deal with the increasingly severe sudden disaster events. Because the distribution of emergency supplies is the key problem for the relief to unexpected disaster events, emergency supplies distribution decision, as an important branch of the emergency management and emergency logistics management, has become a hot issue in academic research at home and abroad.
Firstly, the paper proposed the research thought of emergency supplies optimization distribution decision based on the whole process of the decision in order to provide effective protection for the demand of the emergency supplies based on the analysis of the current research status on emergency decision-making and emergency supplies management in domestic and foreign. Secondly, the paper explained the connotation of emergency supplies distribution decision, analyzed its characteristics and the decision-making process. Lastly and importantly, the paper provided emergency supplies prediction model, emergency supplies distribution models and evaluation model for the decision scheme and their algorithms to the emergency decision-making bodies and staff. The main research content and innovation in this paper are as follows.
(1)Analysis of the characteristics of the emergency supplies distribution decision. Through studying the connotation and the elements of emergency supplies distribution decision system, the characteristics of emergency supplies distribution decision was analyzed from the angle of system elements and the emergency supplies distribution decision-making process was designed. It was believed that emergency supplies distribution decision was a dynamic decision-making process, and the emergency supplies distribution decision-making system was a circulatory system composed of multiple stages. Every decision cycle should include complete four stages, namely, information collection, distribution decision, program evaluation, plan implementation.
(2)Research on the emergency supplies demand forecast model. Based on the different points of supplies demand forecast methods between the emergency logistics situation and general logistics situation, a indirect prediction method was provided to forecast the emergency supplies demand in a gold rescue time after sudden disaster events occurred, namely to forecast the population casualties first, then the emergency supplies demand. Four steps was designed to predict the demand, including qualitative analysis and quantitative analysis of factors associated with injuries population, a BP neural network model to predict the casualty population and the prediction of the emergency supplies demand. According to the four steps, specific models were put forward and described as an example of the emergency supplies demand forecast in a large earthquake.
(3)Research on the optimal emergency supplies distribution model including two stages. The first stage is the building of the model based on two-layer node networks and the game theory. A strategy of so-called incomplete put-out was proposed when relief supplies could not meet the emergency needs within a short time. A non-cooperative game model based on complete information was presented, in which the affected points corresponded to the players, and the distribution schemes to the strategies. A phased planning approach was used to reduce the number of the strategies caused by too many nodes and distribution supplies. The approach can realize the initial distribution of aiming at shorting the response time, and the second planning of establishing a game model for the conflicting nodes after the initial distribution. The Nash equilibrium of the model was found by using particle swarm optimization algorithm through constructing a fitness function. A numerical analysis was conducted to test the effectiveness of the model. The results show that the model does well in distributing the emergency supplies efficiently and fairly when imbalance between supply and demand occurs, and reaches a better rescue effect. The second stage is the building of the distribution model of emergency supplies with three-layer node networks existing in the practice of emergency management. The model aims at minimizing the system losses and meets the constraints of emergency response time and fairness constraint. A modified particle swarm optimization algorithm was proposed for the integer nonlinear programming, the spatial search abilities of the particles were improved by determining different learning objects for different dimensions of the particles. Finally a numerical example was conducted to test the effectiveness of the model and the algorithm.
(4)Research on the evaluation model of emergency supplies distribution scheme. Firstly, the principle on the emergency supplies distribution scheme evaluation should follow was analyzed; it is believed that the principle of fairness should be emphasized when evaluating the emergency supplies distribution scheme after the analysis of the dialectical relationship between impartiality and efficiency; Secondly, the meaning of the fair and the equitable distribution, the connotation of the emergency supplies fair distribution was analyzed; Finally, a simple, easy to understand fair measure model was proposed which took into account the different requirements and urgency degree for supplies. The model was applied to the evaluation of the distribution scheme in the example with three-layer node networks.
The above research can provide scientific basis for emergency supplies distribution decision-making, thereby enhance the operational efficiency of the emergency logistics and emergency supplies support system, and reduce casualties and property losses caused by disasters.
引文
[1]Adivar, B.& Mert, A. International disaster relief planning with fuzzy credibility. Fuzzy Optimization and Decision Making,2010(9),1-21.
[2]Aleskerov, F., Say, A. I.& Toker, A.et al. A cluster-based decision support system for estimating earthquake damage and casualties. Disasters,2005,29(3),255-276.
[3]Allison, P. D. Measures of Inequality. American Sociological Review,1978,43(6), 865-880.
[4]Andersson, T.& Varbrand, P. Decision support tools for ambulance dispatch and relocation. Journal of the Operational Research Society,2007(58),195-207.
[5]Araz, C., Selim, H.& Ozkarahan, I. A fuzzy multi-objective covering-based vehicle location model for emergency services. Computers & Operations Research, 2007(34),705-726.
[6]Atkinson, A. B. On the measurement of inequality. Journal of Economic Theory, 1970(2),244-263.
[7]Badal, J., Zquez-Prada, M.& Gonz A Lez, A. Preliminary quantitative assessment of earthquake casualties and damages. Natural Hazards,2005,34(3),353-374.
[8]Badri, M. A., Mortagy, A. K.& Alsayed, C. A. A multi-objective model for locating fire stations. European Journal of Operational Research,1998(110), 243-260.
[9]Balcik, B.& Beamon, B. M. Facility location in humanitarian relief. International Journal of Logistics:Research and Applications,2008,11(2),101-121.
[10]Barbarosoglu G, Arda Y. A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research Society,2004,55(1),43-53.
[11]Barbarosoglu, G., Ozdamar, L.& Cevik, A. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research,2002(140),118-133.
[12]Blaikei P., Cannon T., Davis I., et al. Risk:Natural hazard, people's vulnerability and Disasters. London: Routledge,1994,147-167.
[13]Chang, M., Tseng, Y.& Chen, J. A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation Research Part E,2007(43),737-754.
[14]Clemmer Elizabeth C. An Investigation into the Relationship of Fairness and Customer Satisfaction with Service.In:Cropanzano Russel 1. ed. Justice in the Workplace, Approaching Justice in Human Resource Management. Hillsdale, NJ:Erlbaum,1993,193-207.
[15]Cosgrave, J. Decision making in emergencies. Disaster Prevention and Management,1996,5(4),28-35.
[16]Dreznera, T., Dreznera, Z.& Guyseb, J. Equitable service by a facility: Minimizing the Gini coefficient. Computers & OperationsResearch,2009(36), 3240-3246.
[17]Eberhart, R. C.& Shi, Y. Particle swarm optimization:developments, application and resources. Seoul, Korea,2001,81-86.
[18]Elliott, R. A measure of fairness of service for scheduling algorithms in multi-user systems. Canadian,2002,1583-1588.
[19]Equi, L., Gallo, G. M.& Marziale, G. A combined transportation and scheduling problem. Pisa, Pisa University,1996,523-538.
[20]Fiedrich, F., Gehbauer, F.& Rickers, U. Optimized resource allocation for emergency response after earthquake disasters. Safety Science,2000(35),41-57.
[21]Gendreau, M., Laporte, G.& Semet, F. A dynamic model and parallel tabu search heuristic for real-time ambulance. Parallel Computing,2001(27), 1641-1653.
[22]Graber, W. K.& Gassmann, F. Real time modelling as an emergency decision support. Mathematics and Computers in Simulation,2000(52),413-426.
[23]Guo, Z.& Qi, M. Research on the Demand Forecast of Emergency Material Based on Fuzzy Markov Chain,2010.
[24]Gupta, U. Multi-event crisis management using non-cooperative repeated games, Doctoral Dissertation, University of South Florida,2004.
[25]Haghani, A., Oh, S.C. Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transportation Research Part A,1996,30(3),231-250.
[26]HernaAndeza, J. Z.& Serrano, J. M. Knowledge-based models for emergency management systems. Expert Systems with Applications,2001(20),173-186.
[27]Ikeda, Y., Beroggi, G. E. G.& Wallace, W. A. Supporting multi-group emergency management with multimedia. Safety Science,1998(30),223-234.
[28]Jain, R., Chiu, D. M.& Hawe, W. A quantitative measure of fairness and discrimination for resource allocation in shared computer systems. DEC Research Report TR-301,1984.
[29]Joseph F.st. Cyr. At risk: natural hazards, people's vulnerability, and disasters. Journal of Homeland Security and Emergency Management,2005,2(2),1-4.
[30]Jotshi, A., QiangGong & RajanBatta. Dispatching and routing of emergency vehicles in disaster mitigation using data. Socio-EconomicPlanningSciences, 2009(43),1-24.
[31]Kalu, I. L., Paudyal, G. N.& Gupta, A. D. Equity and efficiency issues in irrigation water distribution. Agiricultural Water Management,1995(28), 335-348.
[32]Karaman, M. M., Elmaghraby, W.& Salman, F. S. Relief Aid Stocking Decisions under Cooperation of Emergency Response Agencies,2009,1-4.
[33]Klein G. A. Recognition-primed Decisions. Greenwich, CT:JA I Press,1989, 47-92.
[34]Liang, J. J., Qin, A. K. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION,2006,10(3),281-295.
[35]List, G. Routing and emergency-response-team siting for high-level radioactive waste shipments. IEEE Transaction on Engineering Management,1998,45(2), 141-152.
[36]Liu, R. The Water Pollution Emergency Material Requirement Forecast Research of the Three Gorges Reservoir Area,2010,1-4.
[37]Liu, W., Hu, G.& Li, J. Emergency resources demand prediction using case-based reasoning. Safety Science,2012(50),530-534.
[38]Mandell, M. B. Modelling effectiveness-equity trade-offs in public services delivery systems. Management Science,1991,37(4),467-482.
[39]Marsh, M. T.& Schilling, D. A. Equity measurement in facility location analysis: a review and framework. European Journal of Operational Research,1994(74), 1-17.
[40]Mckelvey, R. D.& Mclennan, A. Computation of equilibria in finite games, 1996:87-142.
[41]Mendonca, D., Beroggi, G. E. G.& van Gent, D.et al. Designing gaming simulations for the assessment of group decision support systems in emergency response. Safety Science,2006,44(6),523-535.
[42]Nash, J. Non-cooperative Games. The Annals of Mathematics,1951,54(2), 286-295.
[43]Ozbay, K.& Eren Erman Ozguven, M. S. A Stochastic Humanitarian Inventory Control Model for Disaster Planning. Washington, D.C.,2007.
[44]Ozbay, K., Xiao, W.& Iyigun, C.et al. Probabilistic Programming Models for Response Vehicle Dispatching and resource allocation in t raffic incident management.I&SE:Rutgers University,2004,4-14.
[45]Ozdamar, L., Ekinci, E., Kuciikyazici, B. Emergency logistics planning in natural disasters. Annals of Operations Research,2004,129 (1),217-245.
[46]Parsopoulos, K. E.& Vrahatis, M. N. Recent approaches to global optimization problems through particle swarm optimization. Natural Computing,2002(1), 235-306.
[47]Pavlidis, N. G., Parsopoulos, K. E.& Vrahatis, M. N. Computing nash equilibria through computational intelligence mehtods. Journal of Computational and Applied Mathematics,2005,175,113-136.
[48]Pauwels,N., Van De Walle, B.& Hardeman.F.et al. The implications of irreversibility in emergency response decisions. Theory and Decision,2000(49), 25-51.
[49]Ranganathan, N., Gupta, U.& Shetty, R.et al. An automated decision support system based on game theoretic optimization for emergency management in urban environments. Journal of Homeland Security and Emergency Management,2007,4(2),1-25.
[50]Rathi, A. K., Church, R. L.& Solanki, R. S. Allocating resources to support a multicommodity flow with time windows. Logistics and Transportation Review, 1993(28),167-188.
[51]Rawls, C. G.& Turnquist, M. A. Pre-positioning of emergency supplies for disaster response. Transportation Research Part B,2010(44),521-534.
[52]Ray, J. A multi-period linear programming modal for optimally scheduling the distribution of food-aid in west, Doctoral Dissertation, University of Tennessee, 1987.
[53]Raz, D., Levy, H.& Avi-Itzhak, B. A resource-allocation queueing fairness measure,2004:130-141.
[54]Sayegha, L., Anthony, W. P.& Perrewe, P. L. Managerial Decision- making Under Crisis the Role o f Emotion in an Intuitive Decision Process. Human Resource Management Review,2004(14),179-199.
[55]Shetty, R. S. An event driven single game solution for resource allocation in a multi-crisis environment. Doctoral Dissertation, University of South Florida, 2004.
[56]Sheu, J.B., An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E,2007,43(1), 687-709.
[57]Sheu, J.B., Dynamic relief-demand management for emergency logistics operations under large-scale disasters. Transportation Research Part E:Logistics and Transportation Review,2010,46(1),1-17.
[58]Sheu, J.B., Chen, Y.& Lan, L. W. A novel model for quick response to disaster relief distribution. Proceedings of the Eastern Asia Society for Transportation Studies,2005 (5),2454-2462.
[59]Shi Y. and Eberhart R., A modified particle swarm optimizer. In Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence, 1998,69-73.
[60]Shi Y. and Eberhart R., Empirical study of particle swarm optimization. In Proceedings IEEE Congress. Evolutionary Computation,1999(3),1945-1950.
[61]Tamura, H., Yamamoto, K.& Akazawa, K. Decision Analysis for Mitigating Natural Disaster Risks. Nashville, TN,2000,554-559.
[62]Taskin, S.& Lodree Jr, E. J. Inventory decisions for emergency supplies based on hurricane count predictions. Int. J. Production Economics,2009(126),66-75.
[63]Toregas, C., Swain, R.& ReVelle, C.et al. The Location of Emergency Service Facilities. Operations Research,1971,19(6),1363-1373.
[64]Van Wyk, E., Bean, W. L.& Yadavalli, V. S. S. Modelling of uncertrainty in minimising the cost of inventory for disaster beliefe. South African Journal of Industrial Engineering,2011,22(1),1-11.
[65]Wei Yi, Arun Kumar. Ant colony optimization for disaster relief operations. Transportation Research Part E,2007 (43),660-672.
[66]Wybo, J. L.& Kowalski, K. M. Command centers and emergency management support. Safety Science,1998(30),131-138.
[67]Yang, L., Bryan& Joneset al. A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms. European Journal of Operational Research,2007(182),903-915.
[68]Yi, W.& Kumar, A. Ant colony optimization for disaster relief operation. Transportation Research Part E,2007(43),660-672.
[69]Yi, W.& Ozdamar, L. A dynamic logistics coordination model for evacuation and support in disaster response. European Journal of Operational Research, 2007(179),1177-1193.
[70]Zhou, Y.& Sethu, H. On the relationship between absolute and relative fairness bounds. IEEE COMMUNICATIONS LETTERS,2002,6(1),37-39.
[71]包玉梅.突发公共事件应急物姿储备策略研究.科技信息(学术版),2008(34),67-69.
[72]Briggs S.地震伤亡率的影响因素.中国输血杂志,2008,21(8),643-644
[73]曹书民和杜清玲.基于BP神经网络的人力资源需求预测.山东理工大学学报(自然科学版),2008(5),26-29.
[74]陈安,陈宁,倪慧荟.现代应急管理理论与方法.北京：科学出版社,2009,232,266-267.
[75]陈达强,刘南,缪亚萍.基于成本修正的应急物流物资响应决策模型.东南大学学报(哲学社会科学版),2009(1),67-70.
[76]陈达强,郑文创,丁夏.带时变供求约束的应急物资分配模型.物流技术,2009(2),90-92.
[77]陈棋福.中国震例(1992-1994).北京：地震出版社,2002,117-139,358-390.
[78]陈棋福.中国震例(1997-1999).北京：地震出版社,2003,46-173,245-270,373-399.
[77]陈棋福.中国震例(2000-2002).北京：地震出版社,2008,1-34,280-308,392-425.
[79]陈森,姜江,陈英武.未定路网结构情况下应急物资车辆配送问题模型与应用.系统工程理论与实践,2011(5),907-913.
[80]程序芳.基于需求分级的两次应急资源运输研究.科学技术与工程,2010,10(10),2556-2559.
[81]崔秋文.房屋质量低劣是土耳其地震伤亡惨重的最大元凶.地震科技情报,1999(11),32-35.
[82]桂维民.应急决策论.北京：中共中央党校出版社,2007,100-112.
[83]方磊.基于偏好DEA模型的应急资源优化配置.系统工程理论与实践,2008(8),98-104.
[84]方磊,何建敏.综合AHP和目标规划方法的应急系统选址规划模型.系统工程理论与实践,2003(12),116-120.
[85]方磊,何建敏.城市应急系统优化选址决策模型和算法.管理科学学报,2005(1),12-16.
[86]傅志妍,陈坚.灾害应急物资需求预测模型研究.物流科技,2009(10),11-13.
[87]葛洪磊,刘南,张国川,俞海宏.基于受灾人员损失的多受灾点、多商品应急物资分配模型.系统管理学报,2010,19(5),541-545.
[88]葛洪磊,刘南.基于灾情信息序贯观测的应急物资分配模型.统计与决策,2011(22),46-49.
[89]葛洪磊,刘南.资源分配中的公平测度指标及其选择标准.统计与决策,2012(9),50-53.
[90]国家减灾委员会科学技术部抗震救灾专家组.汶川地震灾害综合分析与评估.北京：科学出版社,2008,3-82.
[91]郭金芬,周刚.大型地震应急物资需求预测方法研究.价值工程,2011,30(22),27-29.
[92]郭平,彭妮娅,侯盾.收入分配公平的衡量-基于等基尼系数线的平均增长点方法研究.财经理论与实践,2009,30(161),81-85.
[93]郭子雪,齐美然,张强.基于区间数的应急物资储备库最小费用选址模型.运筹与管理,2010(1),15-20.
[94]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.软科学,2009(8),50-53.
[95]韩强.一类应急物资调度的双层规划模型及其算法.中国管理科学,2007,15(10),716-719.
[96]胡传平.区域火灾风险评估与灭火救援力量布局优化研究.博士学位论文,同济大学,2006.
[97]华国伟,余乐安,汪寿阳.非常规突发事件特征刻画与应急决策研究.电子科技大学学报(社科版),2011,13(2),33-36.
[98]计雷,池宏,陈安等.突发事件应急管理.北京：高等教育出版社,2006,42-52.
[99]姜涛,朱金福.应急设施鲁棒优化选址模型及算法.交通运输工程学报,2007(5),101-105.
[100]姜艳萍,樊治平,苏明明.应急决策方案的动态调整方法研究.中国管理科学,2011,19(5),104-108.
[101]李进,张江华,朱道立.灾害链中多资源应急调度模型与算法.系统工程理论与实践,2011,31(3),488-495.
[102]李磊.地震应急救援现场需求分析及物资保障.防灾科技学院学报,2006(3),15-18.
[103]李阳,李聚轩,腾立新.大规模灾害救灾物流系统研究.资源与环境,2005,23(7),64-67.
[104]李元佳,张春,宋溢澄.贝叶斯决策理论在核事故中-晚期应急决策优化中的应用.暨南大学学报(自然科学版),2003,24(1),1-6.
[105]刘春林,何建敏,施建军.一类应急物资调度的优化模型研究.中国管理科学,2001(3),30-37.
[106]刘利民,王敏杰.我国应急物资储备优化问题初探.物流科技,2009(2),39-41.
[107]刘明,赵林度.应急物资混合协同配送模式研究.控制与决策,2011(1),96-100.
[108]刘倬,吴忠良.地震和地震海啸中报道死亡人数随时间变化的二个简单模型.中国地震,2005(4),526-529.
[109]刘宗熹,章竞.由汶川地震看应急物资的储备与管理.物流工程与管理,2008(11),52-55.
[11O]廖振良,刘宴辉,徐祖信.基于案例推理的突发性环境污染事件应急预案系统.环境污染与防治,2009(1),86-89.
[111]陆相林,侯云先.基于设施选址理论的中国国家级应急物资储备库配置.经济地理,2010(7),1091-1095.
[112]马玉宏,谢礼立.地震人员伤亡估算方法研究.地震工程与工程振动,2000(4),140-147.
[113]缪成,许维胜,吴启迪.大规模应急救援物资运输模型的构建与求解.系统工程,2006(11),6-12.
[114]聂高众,高建国,苏桂武等.地震应急救助需求的模型化处理—来自地震震例的经验分析.资源科学,2001,23(1),69-76.
[115]乔洪波.应急物资需求分类及需求量研究.硕士学位论文,北京交通大学,2009.
[116]秦军昌,王刊良.一个跨期应急物资库存模型及其解析仿真求解算法.运筹与管理,2008(4),45-50.
[117]盛世明.浅谈不公平程度的度量方法.统计与决策,2004(2),78-79.
[118]史培军.四论灾害系统研究的理论与实践.自然灾害学报,2005(6),1-7.
[119]宋晓宇,刘春会,常春光.基于改进GM11模型的应急物资需求量预测.沈阳建筑大学学报(自然科学版),2010,26(6),1214-1218.
[120]苏博,刘鲁,杨方廷.基于灰色关联分析的神经网络模型.系统工程理论与实践,2008(9),98-104.
[121]孙士宏.震前应急决策的思考.西宁：中国地震局分析预报中心,2002,164.
[122]孙燕娜,王玉海,廖建辉.救灾需求内涵模式及其指标体系与救助评估研究.经济与管理研究,2010(6),85-94.
[123]田军,马文正,汪应洛等.应急物资配送动态调度的粒子群算法.系统工程理论与实践,2011,31(5),898-906.
[124]王波.基于均衡选择的应急物资调度决策模型研究.学理论,2010(17),40-44.
[125]汪季玉,王金桃.基于案例推理的应急决策支持系统研究.管理科学,2003,16(6),46-50.
[126]王楠,刘勇,曾敏刚.自然灾害应急物流的物资分配策略研究.北京：中国物资出版社,2006,518-525.
[127]王晓,庄亚明.基于案例推理的非常规突发事件资源需求预测.西安电子科技大学学报(社会科学版),2010,20(4),22-26.
[128]王新平,王海燕.多疫区多周期应急物资协同优化调度.系统工程理论与实践,2012(2),283-291.
[129]吴国斌,佘廉.突发事件演化模型与应急决策：相关领域研究述评.中国管理科学,2006,14(10),827-830.
[130]吴昊昱.地震死亡人数的分布与震后快速估计的方法研究.硕士学位论文,中国地震局地球物理研究所,2009.
[131]吴新燕,顾建华,吴昊昱.地震报道死亡人数随时间变化的修正指数模型.地震学报,2009(4),457-463.
[132]西蒙赫伯特A.管理行为(原书第4版).北京：机械工业出版社,2010：83-86.
[133]席酉民.管理研究.北京：机械工业出版社,2000,328.
[134]夏萍,刘凯.基于反馈控制原理的应急物资分配动态决策过程分析.物流技术,2011(1),87-89.
[135]夏禹龙,刘吉,冯之浚等.论应急决策.领导科学,1989(5),14-17.
[136]肖新平.关于灰色关联度量化模型的理论研究和评论.系统工程理论与实践,1997(8),77-82.
[137]邢冀,钱新明,刘牧等.基于Visual Basic.NET的油气事故应急资源需求预测支持决策系统.灾害学,2010,25(10),291-295.
[138]徐尚友.公共投资分配效果的评价指标：公平化指数.统计与决策,2007(7),78-79.
[139]杨帆,郑宝柱和剡亮亮.基于BP神经网络的地震伤亡人数评估体系研究.震灾防御技术,2009(4),428-435.
[140]杨继君,吴启迪,程艳等.面向非常规突发事件的应急资源合作博弈调度.系统工程,2008,26(9),21-25.
[141]杨继君,吴启迪,程艳等.面向非常规突发事件的应对方案序贯决策.同济大学学报(自然科学版),2010,38(4),619-624.
[142]杨继君,许维胜,黄武军等.基于多灾点非合作博弈的资源调度建模与仿真.计算机应用,2008,28(6),1620-1623.
[143]杨杰英,李永强,刘丽芳等.地震三要素对地震伤亡人数的影响分析.地震研究,2007(2),182-187.
[144]杨庆育,李明.基于灰色关联分析法的区域自主创新能力实证测度—以重庆市为例.软科学,2011,25(1),91-94,101.
[145]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.系统工程理论与实践,2010,30(7),1218-1226.
[146]姚杰,计雷,池宏.突发事件应急管理中的动态博弈分析.管理评论,2005,17(3),46-50.
[147]于辉,刘洋.应急物资的两阶段局内分配策略.系统工程理论与实践,2011,31(3),394-403.
[148]佘廉,吴国斌.突发事件演化与应急决策研究.交通企业管理,2005(12),4-5.
[149]于瑛英,池宏,祁明亮等.应急管理中资源布局评估与调整的模型和算法.系统工程,2008(1),75-81.
[150]袁辉.重大突发事件及其应急决策研究.安全,1996(2),1-4.
[151]袁一凡.灾害直接损失评估.北京：地震出版社,2007,82-85.
[152]曾伟,周剑岚,王红卫.应急决策的理论与方法探讨.中国安全科学学报,2009(3),172-176.
[153]张波.基于两因素的武警部队应急军需物资需求预测分析.武警工程学院学报,2009,25(4),56-59.
[154]张德丰.MATLAB神经网络应用设计.北京：机械工业出版社,2009,218-224.
[155]张婧,申世飞,杨锐.基于偏好序的多事故应急资源调配博弈模型.清华大学学报(自然科学版),2007,47(12),2172-2175.
[156]张薇.突发事件应急物资储备模型探究.商场现代化,2009(13),130-131.
[157]张维迎.博弈论与信息经济学.上海：格致出版社,2004,25-31.
[158]张小宁,曹津.交通拥挤收费的社会公平性分析.同济大学学报(自然科学版),2010,38(11),1605-1609.
[159]张彦琦,唐贵立,王文昌等.基尼系数和泰尔指数在卫生资源配置公平性研究中的应用.中国卫生统计,2008(3),243-246.
[160]张泽旭.神经网络控制与MATLAB仿真.哈尔滨：哈尔滨工业大学出版社,2011,56-61.
[161]张肇诚.中国震例(1966-975).北京：地震出版社,1988,57-76,98-116,155-177,189-210.
[162]张肇诚.中国震例(1976-980).北京：地震出版社,1990,29-133,146-164,302-326.
[163]张肇诚.中国震例(1981-1985).北京：地震出版社,1990,1-14,109-117,240-266.
[164]张自立,李向阳,王桂森.基于生产能力储备的应急物资协议企业选择研究.运筹与管理,2009(1),146-150.
[165]赵林度.城市群协同应急决策生成理论研究.东南大学学报(哲学社会科学版),2009(1),49-55.
[166]赵淑红.应急管理中的动态博弈模型及应用.硕士学位论文,河南大学,2007.
[167]赵希男,靖可,陈周坤.基于个体特征识别的应急决策有效性评价方法.系统工程,2009(7),75-80.
[168]周涛,李臻洋.基于灰色关联分析法的高校“211”工程管理模式研究.华北电力大学学报(社会科学版),2010(1),125-127.
[169]邹其嘉,毛国敏,孙振凯等.地震人员伤亡易损性研究.自然灾害学报,1995(3),60-68.
[2]Aleskerov, F., Say, A. I.& Toker, A.et al. A cluster-based decision support system for estimating earthquake damage and casualties. Disasters,2005,29(3),255-276.
[3]Allison, P. D. Measures of Inequality. American Sociological Review,1978,43(6), 865-880.
[4]Andersson, T.& Varbrand, P. Decision support tools for ambulance dispatch and relocation. Journal of the Operational Research Society,2007(58),195-207.
[5]Araz, C., Selim, H.& Ozkarahan, I. A fuzzy multi-objective covering-based vehicle location model for emergency services. Computers & Operations Research, 2007(34),705-726.
[6]Atkinson, A. B. On the measurement of inequality. Journal of Economic Theory, 1970(2),244-263.
[7]Badal, J., Zquez-Prada, M.& Gonz A Lez, A. Preliminary quantitative assessment of earthquake casualties and damages. Natural Hazards,2005,34(3),353-374.
[8]Badri, M. A., Mortagy, A. K.& Alsayed, C. A. A multi-objective model for locating fire stations. European Journal of Operational Research,1998(110), 243-260.
[9]Balcik, B.& Beamon, B. M. Facility location in humanitarian relief. International Journal of Logistics:Research and Applications,2008,11(2),101-121.
[10]Barbarosoglu G, Arda Y. A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research Society,2004,55(1),43-53.
[11]Barbarosoglu, G., Ozdamar, L.& Cevik, A. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research,2002(140),118-133.
[12]Blaikei P., Cannon T., Davis I., et al. Risk:Natural hazard, people's vulnerability and Disasters. London: Routledge,1994,147-167.
[13]Chang, M., Tseng, Y.& Chen, J. A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation Research Part E,2007(43),737-754.
[14]Clemmer Elizabeth C. An Investigation into the Relationship of Fairness and Customer Satisfaction with Service.In:Cropanzano Russel 1. ed. Justice in the Workplace, Approaching Justice in Human Resource Management. Hillsdale, NJ:Erlbaum,1993,193-207.
[15]Cosgrave, J. Decision making in emergencies. Disaster Prevention and Management,1996,5(4),28-35.
[16]Dreznera, T., Dreznera, Z.& Guyseb, J. Equitable service by a facility: Minimizing the Gini coefficient. Computers & OperationsResearch,2009(36), 3240-3246.
[17]Eberhart, R. C.& Shi, Y. Particle swarm optimization:developments, application and resources. Seoul, Korea,2001,81-86.
[18]Elliott, R. A measure of fairness of service for scheduling algorithms in multi-user systems. Canadian,2002,1583-1588.
[19]Equi, L., Gallo, G. M.& Marziale, G. A combined transportation and scheduling problem. Pisa, Pisa University,1996,523-538.
[20]Fiedrich, F., Gehbauer, F.& Rickers, U. Optimized resource allocation for emergency response after earthquake disasters. Safety Science,2000(35),41-57.
[21]Gendreau, M., Laporte, G.& Semet, F. A dynamic model and parallel tabu search heuristic for real-time ambulance. Parallel Computing,2001(27), 1641-1653.
[22]Graber, W. K.& Gassmann, F. Real time modelling as an emergency decision support. Mathematics and Computers in Simulation,2000(52),413-426.
[23]Guo, Z.& Qi, M. Research on the Demand Forecast of Emergency Material Based on Fuzzy Markov Chain,2010.
[24]Gupta, U. Multi-event crisis management using non-cooperative repeated games, Doctoral Dissertation, University of South Florida,2004.
[25]Haghani, A., Oh, S.C. Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transportation Research Part A,1996,30(3),231-250.
[26]HernaAndeza, J. Z.& Serrano, J. M. Knowledge-based models for emergency management systems. Expert Systems with Applications,2001(20),173-186.
[27]Ikeda, Y., Beroggi, G. E. G.& Wallace, W. A. Supporting multi-group emergency management with multimedia. Safety Science,1998(30),223-234.
[28]Jain, R., Chiu, D. M.& Hawe, W. A quantitative measure of fairness and discrimination for resource allocation in shared computer systems. DEC Research Report TR-301,1984.
[29]Joseph F.st. Cyr. At risk: natural hazards, people's vulnerability, and disasters. Journal of Homeland Security and Emergency Management,2005,2(2),1-4.
[30]Jotshi, A., QiangGong & RajanBatta. Dispatching and routing of emergency vehicles in disaster mitigation using data. Socio-EconomicPlanningSciences, 2009(43),1-24.
[31]Kalu, I. L., Paudyal, G. N.& Gupta, A. D. Equity and efficiency issues in irrigation water distribution. Agiricultural Water Management,1995(28), 335-348.
[32]Karaman, M. M., Elmaghraby, W.& Salman, F. S. Relief Aid Stocking Decisions under Cooperation of Emergency Response Agencies,2009,1-4.
[33]Klein G. A. Recognition-primed Decisions. Greenwich, CT:JA I Press,1989, 47-92.
[34]Liang, J. J., Qin, A. K. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION,2006,10(3),281-295.
[35]List, G. Routing and emergency-response-team siting for high-level radioactive waste shipments. IEEE Transaction on Engineering Management,1998,45(2), 141-152.
[36]Liu, R. The Water Pollution Emergency Material Requirement Forecast Research of the Three Gorges Reservoir Area,2010,1-4.
[37]Liu, W., Hu, G.& Li, J. Emergency resources demand prediction using case-based reasoning. Safety Science,2012(50),530-534.
[38]Mandell, M. B. Modelling effectiveness-equity trade-offs in public services delivery systems. Management Science,1991,37(4),467-482.
[39]Marsh, M. T.& Schilling, D. A. Equity measurement in facility location analysis: a review and framework. European Journal of Operational Research,1994(74), 1-17.
[40]Mckelvey, R. D.& Mclennan, A. Computation of equilibria in finite games, 1996:87-142.
[41]Mendonca, D., Beroggi, G. E. G.& van Gent, D.et al. Designing gaming simulations for the assessment of group decision support systems in emergency response. Safety Science,2006,44(6),523-535.
[42]Nash, J. Non-cooperative Games. The Annals of Mathematics,1951,54(2), 286-295.
[43]Ozbay, K.& Eren Erman Ozguven, M. S. A Stochastic Humanitarian Inventory Control Model for Disaster Planning. Washington, D.C.,2007.
[44]Ozbay, K., Xiao, W.& Iyigun, C.et al. Probabilistic Programming Models for Response Vehicle Dispatching and resource allocation in t raffic incident management.I&SE:Rutgers University,2004,4-14.
[45]Ozdamar, L., Ekinci, E., Kuciikyazici, B. Emergency logistics planning in natural disasters. Annals of Operations Research,2004,129 (1),217-245.
[46]Parsopoulos, K. E.& Vrahatis, M. N. Recent approaches to global optimization problems through particle swarm optimization. Natural Computing,2002(1), 235-306.
[47]Pavlidis, N. G., Parsopoulos, K. E.& Vrahatis, M. N. Computing nash equilibria through computational intelligence mehtods. Journal of Computational and Applied Mathematics,2005,175,113-136.
[48]Pauwels,N., Van De Walle, B.& Hardeman.F.et al. The implications of irreversibility in emergency response decisions. Theory and Decision,2000(49), 25-51.
[49]Ranganathan, N., Gupta, U.& Shetty, R.et al. An automated decision support system based on game theoretic optimization for emergency management in urban environments. Journal of Homeland Security and Emergency Management,2007,4(2),1-25.
[50]Rathi, A. K., Church, R. L.& Solanki, R. S. Allocating resources to support a multicommodity flow with time windows. Logistics and Transportation Review, 1993(28),167-188.
[51]Rawls, C. G.& Turnquist, M. A. Pre-positioning of emergency supplies for disaster response. Transportation Research Part B,2010(44),521-534.
[52]Ray, J. A multi-period linear programming modal for optimally scheduling the distribution of food-aid in west, Doctoral Dissertation, University of Tennessee, 1987.
[53]Raz, D., Levy, H.& Avi-Itzhak, B. A resource-allocation queueing fairness measure,2004:130-141.
[54]Sayegha, L., Anthony, W. P.& Perrewe, P. L. Managerial Decision- making Under Crisis the Role o f Emotion in an Intuitive Decision Process. Human Resource Management Review,2004(14),179-199.
[55]Shetty, R. S. An event driven single game solution for resource allocation in a multi-crisis environment. Doctoral Dissertation, University of South Florida, 2004.
[56]Sheu, J.B., An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E,2007,43(1), 687-709.
[57]Sheu, J.B., Dynamic relief-demand management for emergency logistics operations under large-scale disasters. Transportation Research Part E:Logistics and Transportation Review,2010,46(1),1-17.
[58]Sheu, J.B., Chen, Y.& Lan, L. W. A novel model for quick response to disaster relief distribution. Proceedings of the Eastern Asia Society for Transportation Studies,2005 (5),2454-2462.
[59]Shi Y. and Eberhart R., A modified particle swarm optimizer. In Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence, 1998,69-73.
[60]Shi Y. and Eberhart R., Empirical study of particle swarm optimization. In Proceedings IEEE Congress. Evolutionary Computation,1999(3),1945-1950.
[61]Tamura, H., Yamamoto, K.& Akazawa, K. Decision Analysis for Mitigating Natural Disaster Risks. Nashville, TN,2000,554-559.
[62]Taskin, S.& Lodree Jr, E. J. Inventory decisions for emergency supplies based on hurricane count predictions. Int. J. Production Economics,2009(126),66-75.
[63]Toregas, C., Swain, R.& ReVelle, C.et al. The Location of Emergency Service Facilities. Operations Research,1971,19(6),1363-1373.
[64]Van Wyk, E., Bean, W. L.& Yadavalli, V. S. S. Modelling of uncertrainty in minimising the cost of inventory for disaster beliefe. South African Journal of Industrial Engineering,2011,22(1),1-11.
[65]Wei Yi, Arun Kumar. Ant colony optimization for disaster relief operations. Transportation Research Part E,2007 (43),660-672.
[66]Wybo, J. L.& Kowalski, K. M. Command centers and emergency management support. Safety Science,1998(30),131-138.
[67]Yang, L., Bryan& Joneset al. A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms. European Journal of Operational Research,2007(182),903-915.
[68]Yi, W.& Kumar, A. Ant colony optimization for disaster relief operation. Transportation Research Part E,2007(43),660-672.
[69]Yi, W.& Ozdamar, L. A dynamic logistics coordination model for evacuation and support in disaster response. European Journal of Operational Research, 2007(179),1177-1193.
[70]Zhou, Y.& Sethu, H. On the relationship between absolute and relative fairness bounds. IEEE COMMUNICATIONS LETTERS,2002,6(1),37-39.
[71]包玉梅.突发公共事件应急物姿储备策略研究.科技信息(学术版),2008(34),67-69.
[72]Briggs S.地震伤亡率的影响因素.中国输血杂志,2008,21(8),643-644
[73]曹书民和杜清玲.基于BP神经网络的人力资源需求预测.山东理工大学学报(自然科学版),2008(5),26-29.
[74]陈安,陈宁,倪慧荟.现代应急管理理论与方法.北京：科学出版社,2009,232,266-267.
[75]陈达强,刘南,缪亚萍.基于成本修正的应急物流物资响应决策模型.东南大学学报(哲学社会科学版),2009(1),67-70.
[76]陈达强,郑文创,丁夏.带时变供求约束的应急物资分配模型.物流技术,2009(2),90-92.
[77]陈棋福.中国震例(1992-1994).北京：地震出版社,2002,117-139,358-390.
[78]陈棋福.中国震例(1997-1999).北京：地震出版社,2003,46-173,245-270,373-399.
[77]陈棋福.中国震例(2000-2002).北京：地震出版社,2008,1-34,280-308,392-425.
[79]陈森,姜江,陈英武.未定路网结构情况下应急物资车辆配送问题模型与应用.系统工程理论与实践,2011(5),907-913.
[80]程序芳.基于需求分级的两次应急资源运输研究.科学技术与工程,2010,10(10),2556-2559.
[81]崔秋文.房屋质量低劣是土耳其地震伤亡惨重的最大元凶.地震科技情报,1999(11),32-35.
[82]桂维民.应急决策论.北京：中共中央党校出版社,2007,100-112.
[83]方磊.基于偏好DEA模型的应急资源优化配置.系统工程理论与实践,2008(8),98-104.
[84]方磊,何建敏.综合AHP和目标规划方法的应急系统选址规划模型.系统工程理论与实践,2003(12),116-120.
[85]方磊,何建敏.城市应急系统优化选址决策模型和算法.管理科学学报,2005(1),12-16.
[86]傅志妍,陈坚.灾害应急物资需求预测模型研究.物流科技,2009(10),11-13.
[87]葛洪磊,刘南,张国川,俞海宏.基于受灾人员损失的多受灾点、多商品应急物资分配模型.系统管理学报,2010,19(5),541-545.
[88]葛洪磊,刘南.基于灾情信息序贯观测的应急物资分配模型.统计与决策,2011(22),46-49.
[89]葛洪磊,刘南.资源分配中的公平测度指标及其选择标准.统计与决策,2012(9),50-53.
[90]国家减灾委员会科学技术部抗震救灾专家组.汶川地震灾害综合分析与评估.北京：科学出版社,2008,3-82.
[91]郭金芬,周刚.大型地震应急物资需求预测方法研究.价值工程,2011,30(22),27-29.
[92]郭平,彭妮娅,侯盾.收入分配公平的衡量-基于等基尼系数线的平均增长点方法研究.财经理论与实践,2009,30(161),81-85.
[93]郭子雪,齐美然,张强.基于区间数的应急物资储备库最小费用选址模型.运筹与管理,2010(1),15-20.
[94]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.软科学,2009(8),50-53.
[95]韩强.一类应急物资调度的双层规划模型及其算法.中国管理科学,2007,15(10),716-719.
[96]胡传平.区域火灾风险评估与灭火救援力量布局优化研究.博士学位论文,同济大学,2006.
[97]华国伟,余乐安,汪寿阳.非常规突发事件特征刻画与应急决策研究.电子科技大学学报(社科版),2011,13(2),33-36.
[98]计雷,池宏,陈安等.突发事件应急管理.北京：高等教育出版社,2006,42-52.
[99]姜涛,朱金福.应急设施鲁棒优化选址模型及算法.交通运输工程学报,2007(5),101-105.
[100]姜艳萍,樊治平,苏明明.应急决策方案的动态调整方法研究.中国管理科学,2011,19(5),104-108.
[101]李进,张江华,朱道立.灾害链中多资源应急调度模型与算法.系统工程理论与实践,2011,31(3),488-495.
[102]李磊.地震应急救援现场需求分析及物资保障.防灾科技学院学报,2006(3),15-18.
[103]李阳,李聚轩,腾立新.大规模灾害救灾物流系统研究.资源与环境,2005,23(7),64-67.
[104]李元佳,张春,宋溢澄.贝叶斯决策理论在核事故中-晚期应急决策优化中的应用.暨南大学学报(自然科学版),2003,24(1),1-6.
[105]刘春林,何建敏,施建军.一类应急物资调度的优化模型研究.中国管理科学,2001(3),30-37.
[106]刘利民,王敏杰.我国应急物资储备优化问题初探.物流科技,2009(2),39-41.
[107]刘明,赵林度.应急物资混合协同配送模式研究.控制与决策,2011(1),96-100.
[108]刘倬,吴忠良.地震和地震海啸中报道死亡人数随时间变化的二个简单模型.中国地震,2005(4),526-529.
[109]刘宗熹,章竞.由汶川地震看应急物资的储备与管理.物流工程与管理,2008(11),52-55.
[11O]廖振良,刘宴辉,徐祖信.基于案例推理的突发性环境污染事件应急预案系统.环境污染与防治,2009(1),86-89.
[111]陆相林,侯云先.基于设施选址理论的中国国家级应急物资储备库配置.经济地理,2010(7),1091-1095.
[112]马玉宏,谢礼立.地震人员伤亡估算方法研究.地震工程与工程振动,2000(4),140-147.
[113]缪成,许维胜,吴启迪.大规模应急救援物资运输模型的构建与求解.系统工程,2006(11),6-12.
[114]聂高众,高建国,苏桂武等.地震应急救助需求的模型化处理—来自地震震例的经验分析.资源科学,2001,23(1),69-76.
[115]乔洪波.应急物资需求分类及需求量研究.硕士学位论文,北京交通大学,2009.
[116]秦军昌,王刊良.一个跨期应急物资库存模型及其解析仿真求解算法.运筹与管理,2008(4),45-50.
[117]盛世明.浅谈不公平程度的度量方法.统计与决策,2004(2),78-79.
[118]史培军.四论灾害系统研究的理论与实践.自然灾害学报,2005(6),1-7.
[119]宋晓宇,刘春会,常春光.基于改进GM11模型的应急物资需求量预测.沈阳建筑大学学报(自然科学版),2010,26(6),1214-1218.
[120]苏博,刘鲁,杨方廷.基于灰色关联分析的神经网络模型.系统工程理论与实践,2008(9),98-104.
[121]孙士宏.震前应急决策的思考.西宁：中国地震局分析预报中心,2002,164.
[122]孙燕娜,王玉海,廖建辉.救灾需求内涵模式及其指标体系与救助评估研究.经济与管理研究,2010(6),85-94.
[123]田军,马文正,汪应洛等.应急物资配送动态调度的粒子群算法.系统工程理论与实践,2011,31(5),898-906.
[124]王波.基于均衡选择的应急物资调度决策模型研究.学理论,2010(17),40-44.
[125]汪季玉,王金桃.基于案例推理的应急决策支持系统研究.管理科学,2003,16(6),46-50.
[126]王楠,刘勇,曾敏刚.自然灾害应急物流的物资分配策略研究.北京：中国物资出版社,2006,518-525.
[127]王晓,庄亚明.基于案例推理的非常规突发事件资源需求预测.西安电子科技大学学报(社会科学版),2010,20(4),22-26.
[128]王新平,王海燕.多疫区多周期应急物资协同优化调度.系统工程理论与实践,2012(2),283-291.
[129]吴国斌,佘廉.突发事件演化模型与应急决策：相关领域研究述评.中国管理科学,2006,14(10),827-830.
[130]吴昊昱.地震死亡人数的分布与震后快速估计的方法研究.硕士学位论文,中国地震局地球物理研究所,2009.
[131]吴新燕,顾建华,吴昊昱.地震报道死亡人数随时间变化的修正指数模型.地震学报,2009(4),457-463.
[132]西蒙赫伯特A.管理行为(原书第4版).北京：机械工业出版社,2010：83-86.
[133]席酉民.管理研究.北京：机械工业出版社,2000,328.
[134]夏萍,刘凯.基于反馈控制原理的应急物资分配动态决策过程分析.物流技术,2011(1),87-89.
[135]夏禹龙,刘吉,冯之浚等.论应急决策.领导科学,1989(5),14-17.
[136]肖新平.关于灰色关联度量化模型的理论研究和评论.系统工程理论与实践,1997(8),77-82.
[137]邢冀,钱新明,刘牧等.基于Visual Basic.NET的油气事故应急资源需求预测支持决策系统.灾害学,2010,25(10),291-295.
[138]徐尚友.公共投资分配效果的评价指标：公平化指数.统计与决策,2007(7),78-79.
[139]杨帆,郑宝柱和剡亮亮.基于BP神经网络的地震伤亡人数评估体系研究.震灾防御技术,2009(4),428-435.
[140]杨继君,吴启迪,程艳等.面向非常规突发事件的应急资源合作博弈调度.系统工程,2008,26(9),21-25.
[141]杨继君,吴启迪,程艳等.面向非常规突发事件的应对方案序贯决策.同济大学学报(自然科学版),2010,38(4),619-624.
[142]杨继君,许维胜,黄武军等.基于多灾点非合作博弈的资源调度建模与仿真.计算机应用,2008,28(6),1620-1623.
[143]杨杰英,李永强,刘丽芳等.地震三要素对地震伤亡人数的影响分析.地震研究,2007(2),182-187.
[144]杨庆育,李明.基于灰色关联分析法的区域自主创新能力实证测度—以重庆市为例.软科学,2011,25(1),91-94,101.
[145]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.系统工程理论与实践,2010,30(7),1218-1226.
[146]姚杰,计雷,池宏.突发事件应急管理中的动态博弈分析.管理评论,2005,17(3),46-50.
[147]于辉,刘洋.应急物资的两阶段局内分配策略.系统工程理论与实践,2011,31(3),394-403.
[148]佘廉,吴国斌.突发事件演化与应急决策研究.交通企业管理,2005(12),4-5.
[149]于瑛英,池宏,祁明亮等.应急管理中资源布局评估与调整的模型和算法.系统工程,2008(1),75-81.
[150]袁辉.重大突发事件及其应急决策研究.安全,1996(2),1-4.
[151]袁一凡.灾害直接损失评估.北京：地震出版社,2007,82-85.
[152]曾伟,周剑岚,王红卫.应急决策的理论与方法探讨.中国安全科学学报,2009(3),172-176.
[153]张波.基于两因素的武警部队应急军需物资需求预测分析.武警工程学院学报,2009,25(4),56-59.
[154]张德丰.MATLAB神经网络应用设计.北京：机械工业出版社,2009,218-224.
[155]张婧,申世飞,杨锐.基于偏好序的多事故应急资源调配博弈模型.清华大学学报(自然科学版),2007,47(12),2172-2175.
[156]张薇.突发事件应急物资储备模型探究.商场现代化,2009(13),130-131.
[157]张维迎.博弈论与信息经济学.上海：格致出版社,2004,25-31.
[158]张小宁,曹津.交通拥挤收费的社会公平性分析.同济大学学报(自然科学版),2010,38(11),1605-1609.
[159]张彦琦,唐贵立,王文昌等.基尼系数和泰尔指数在卫生资源配置公平性研究中的应用.中国卫生统计,2008(3),243-246.
[160]张泽旭.神经网络控制与MATLAB仿真.哈尔滨：哈尔滨工业大学出版社,2011,56-61.
[161]张肇诚.中国震例(1966-975).北京：地震出版社,1988,57-76,98-116,155-177,189-210.
[162]张肇诚.中国震例(1976-980).北京：地震出版社,1990,29-133,146-164,302-326.
[163]张肇诚.中国震例(1981-1985).北京：地震出版社,1990,1-14,109-117,240-266.
[164]张自立,李向阳,王桂森.基于生产能力储备的应急物资协议企业选择研究.运筹与管理,2009(1),146-150.
[165]赵林度.城市群协同应急决策生成理论研究.东南大学学报(哲学社会科学版),2009(1),49-55.
[166]赵淑红.应急管理中的动态博弈模型及应用.硕士学位论文,河南大学,2007.
[167]赵希男,靖可,陈周坤.基于个体特征识别的应急决策有效性评价方法.系统工程,2009(7),75-80.
[168]周涛,李臻洋.基于灰色关联分析法的高校“211”工程管理模式研究.华北电力大学学报(社会科学版),2010(1),125-127.
[169]邹其嘉,毛国敏,孙振凯等.地震人员伤亡易损性研究.自然灾害学报,1995(3),60-68.