自然灾害区域疏散的预警优化模型研究

在可预知的灾害来临前,交通堵塞问题是影响应急疏散效率的主要因素。在灾前防御阶段,有策略的发布预警消息可以使疏散更加有秩序的进行,从而提高疏散效率。本文为区域应急疏散预案构建了应急疏散预警发布研究框架,首先建立了避难点分配模型,将其结果代入到疏散预警模型,来优化特定地区预警发布时间和类型。其中,预警模型加入了时间成分,构建成了多时段模型,并使用贪婪的启发式搜索过程求解非线性的公式。最后,通过算例分析了模型算法的应用范围及其可行性,并用模拟退火算法进行了计算,验证了本算法的有效性。本研究更改以往在同一时间通过全部渠道发布消息的方式,通过疏散预警信息的发布策略的优化,可以有效避免在区域内大规模人群同时出发所导致的交通拥堵现象,为政府制定科学的应急疏散预案提供理论和技术支持。     

Generating feasible strategies in nuclear emergencies—a constraint satisfaction problem

RODOS is a Real-time On-line DecisiOn Support system intended for use throughout a nuclear emergency, extending into the longer term. In this paper we concentrate on the early phases in which decisions on sheltering and evacuation have to be taken quickly and under many pressures. RODOS is designed to assist off-site emergency management by formulating and structuring the evaluation of possible combinations of countermeasures. Because there can be very many such combinations to be evaluated, an expert system has been developed to eliminate those that do not satisfy certain constraints depending on factors such as the wind direction and evacuation practicalities. The system uses the ILOG solver constraint satisfaction package and its high-level programming library to reduce the number of strategies to a manageable fraction. This allows a later careful evaluation of the remaining alternatives.     

Assessing systems for offshore emergency evacuation

Emergency evacuation is a rare event in the offshore oil industry. Nonetheless, emergency procedures must be practiced routinely for the benefit of the work force and the emergency services. These practices typically take place in good weather conditions where there is little threat to those involved. However, in reality an emergency could occur in adverse weather conditions which can affect the capabilities of vessels and helicopters. This paper describes a study in which the data from various sources are synthesised in order to estimate the effectiveness of emergency evacuation and rescue systems in a stochastic environment. The study employed a discrete event simulation incorporating a model of the evacuation and rescue operations interfaced with a file of weather data. This approach provided a measure, the probability of completing the evacuation within N hours, for the comparison of alternative systems.     

The Australian National Bushfire model project

The National Bushfire Research Unit has developed a personal computer based model to act as a shell for a decision support system for bushfire management. To date the fire spread module has been developed, and there is a continuing programme to incorporate expert systems. The model is designed for real-time operation. Inputs to the model combine a geographic information system (GIS) with real-time data acquisition and data assimilation through modem connections to telephone lines. Outputs are graphical and allow the fire-front position, which is generated using Huygens' principle, to be examined at any desired scale.     

基于情景分析的应急疏散车辆配置模型

在情景模式影响疏散点疏散人员数量及疏散最晚完成时间限制的条件下,研究了避难所应急疏散车辆配置计划及各种情景模式下的车辆出车任务安排,以疏散车辆出车安排为下层模型,以期望疏散总时间最小化车辆配置计划为上层模型建立了车辆配置及出车任务安排的双层规划模型。设计了结合CPLEX内置算法的模拟退火算法,最后用算例进行了仿真研究。     

基于Agent-DEVS的应急物资保障多分辨率建模研究

多分辨率(Multi-resolution,MR)建模是复杂自适应系统建模和分布式仿真发展急需解决的现实问题,在分析多分辨率模型组织结构和演化方式的基础上,对Agent-DEVS规范进行扩展,加入多分辨率建模层级和相关元组,建立了MR-Agent-DEVS建模规范。将MR-Agent-DEVS引入应急物资保障的仿真建模,完成了耦合模型与仿真流程设计,以及成员模型与典型消息设计。实验结果表明:MR-Agent-DEVS模型能够仿真应急物资保障行为,较聚合解聚法、视点选择法而言,对分辨率控制的时效性更强,灵活性更大,一致性较好,更有利于降低系统负载;与Agent-DEVS模型相比,虽然多分辨率控制在一定程度上增加了模型复杂度,但两者的执行效率基本相当,从而验证了MR-Agent-DEVS模型的实用性。     

Decision support for hospital evacuation and emergency response

Evacuation planning is an important part of a hospital’s emergency management plan. In an evacuation the safety and health of patients is the fundamental success parameter. Thus, in this paper we introduce an evacuation model, appropriate for planning and operations, that has the objective of minimizing expected risk, both the threat risk that is forcing the evacuation, and the risk inherent in transporting patients, some in critical condition. Specifically, we study the allocation of patients, categorized by criticality and care requirements, to a limited fleet of vehicles of various capacities and medical capabilities, to be transported to appropriate receiving hospitals considering the current available space in each hospital for each category of patient. The model is an integer program, where the non-linear expected risks are calculated a-priori. This model has a structure that has excellent solution characteristics that permit us to solve large problems in a reasonable time, enabling the model to potentially be used for both planning and operations. To illustrate the solvability of this model and demonstrate its characteristics, we apply it to a realistic case study based on the evacuation of a large regional hospital.     

A dynamic logistics coordination model for evacuation and support in disaster response activities

This paper describes an integrated location-distribution model for coordinating logistics support and evacuation operations in disaster response activities. Logistics planning in emergencies involves dispatching commodities (e.g., medical materials and personnel, specialised rescue equipment and rescue teams, food, etc.) to distribution centres in affected areas and evacuation and transfer of wounded people to emergency units. During the initial response time it is also necessary to set up temporary emergency centers and shelters in affected areas to speed up medical care for less heavily wounded survivors. In risk mitigation studies for natural disasters, possible sites where these units can be situated are specified according to risk based urban structural analysis. Logistics coordination in disasters involves the selection of sites that result in maximum coverage of medical need in affected areas. Another important issue that arises in such emergencies is that medical personnel who are on duty in nearby hospitals have to be re-shuffled to serve both temporary and permanent emergency units. Thus, an optimal medical personnel allocation must be determined among these units. The proposed model also considers this issue.     

烟羽应急计划区公众撤离模式研究

公众撤离是烟羽应急计划区应急响应状态下的重要安全措施。本文提出一种“政府组织撤离+政府指导下的自行撤离”的撤离模式, 并基于元胞传输理论, 以最小化撤离时间为目标, 建立了公众撤离模型, 规划车辆行驶路线。运用该模型, 分析撤离时间随政府组织撤离和居民自行撤离比例变化的规律, 并运用到两个案例中, 结果显示:“政府组织撤离+政府指导下的自行撤离”模式的撤离时间小于“政府组织撤离”模式的撤离时间, 而且政府组织撤离与自行撤离之间存在一个最佳的比例结构, 使撤离时间达到相对低的水平。 关键词:烟羽应急计划区;公众撤离;元胞传输理论;模式研究;应急管理     

Modeling framework for optimal evacuation of large-scale crowded pedestrian facilities

The paper presents a simulation–optimization modeling framework for the evacuation of large-scale pedestrian facilities with multiple exit gates. The framework integrates a genetic algorithm (GA) and a microscopic pedestrian simulation–assignment model. The GA searches for the optimal evacuation plan, while the simulation model guides the search through evaluating the quality of the generated evacuation plans. Evacuees are assumed to receive evacuation instructions in terms of the optimal exit gates and evacuation start times. The framework is applied to develop an optimal evacuation plan for a hypothetical crowded exhibition hall. The obtained results show that the model converges to a superior optimal evacuation plan within an acceptable number of iterations. In addition, the obtained evacuation plan outperforms conventional plans that implement nearest-gate immediate evacuation strategies.     

基于GIS的河道、蓄滞洪区洪水演进动态可视化仿真研究

结合地理信息系统(GIS)技术和三维仿真图示技术,探讨了基于GIS的河道、蓄滞洪区洪水演进可视化仿真技术原理与方法,分析了洪水演进可视化模型的建立过程,设计出河道、蓄滞洪区洪水演进系统的总体结构及开发模式,并介绍了系统具体功能的实现.本仿真模型在实例中得到了成功的应用,可为防洪减灾决策提供快捷、直观形象的信息支持.     

Dynamic navigation field in the social force model for pedestrian evacuation

This paper presents a generalized walking cost distribution to determine a dynamic navigation field in the social force model for pedestrian evacuation. The local walking cost per unit distance of movement includes the cost associated with travel time and other additional costs incurred by pedestrians to avoid colliding with obstacles in a dynamic environment. In the dynamic navigation field, pedestrians expect to choose an optimal path with the lowest walking cost to reach their target destination reactively based on available instantaneous information. The social force model with the dynamic navigation field is validated by comparing the simulation results with empirical observations. The fundamental diagrams for observations and simulation data agree well, which indicates the effectiveness of the model. Numerical results show that the model with the dynamic navigation field can reproduce typical stages of the dynamics of pedestrian evacuation, such as self-organized arching and queuing phenomena, and can capture the route choice and exit choice behaviors of pedestrians during the evacuation process. Compared to the model with the static navigation field, the model with the dynamic navigation field can reduce the total evacuation time of the room and save the required CPU time for a large group of pedestrians. Furthermore, the strong tendency to avoid local high-density regions (i.e., minimizing collisions) can also reduce the total evacuation time under the same conditions.     

Simulation optimization for an emergency department healthcare unit in Kuwait

This paper integrates simulation with optimization to design a decision support tool for the operation of an emergency department unit at a governmental hospital in Kuwait. The hospital provides a set of services for different categories of patients. We present a methodology that uses system simulation combined with optimization to determine the optimal number of doctors, lab technicians and nurses required to maximize patient throughput and to reduce patient time in the system subject to budget restrictions. The major objective of this decision supporting tool is to evaluate the impact of various staffing levels on service efficiency. Experimental results show that by using current hospital resources, the optimization simulation model generates optimal staffing allocation that would allow 28% increase in patient throughput and an average of 40% reduction in patients’ waiting time.     

Simulation-based framework to improve patient experience in an emergency department

The global economic crisis has a significant impact on healthcare resource provision worldwide. The management of limited healthcare resources is further challenged by the high level of uncertainty in demand, which can lead to unbalanced utilization of the available resources and a potential deterioration of patient satisfaction in terms of longer waiting times and perceived reduced quality of services. Therefore, healthcare managers require timely and accurate tools to optimize resource utility in a complex and ever-changing patient care process. An interactive simulation-based decision support framework is presented in this paper for healthcare process improvement. Complexity and different levels of variability within the process are incorporated into the process modeling phase, followed by developing a simulation model to examine the impact of potential alternatives. As a performance management tool, balanced scorecard (BSC) is incorporated within the framework to support continual and sustainable improvement by using strategic-linked performance measures and actions. These actions are evaluated by the simulation model developed, whilst the trade-off between objectives, though somewhat conflicting, is analysed by a preference model. The preference model is designed in an interactive and iterative process considering decision makers preferences regarding the selected key performance indicators (KPIs). A detailed implementation of the framework is demonstrated on an emergency department (ED) of an adult teaching hospital in north Dublin, Ireland. The results show that the unblocking of ED outflows by in-patient bed management is more effective than increasing only the ED physical capacity or the ED workforce.     

一线救治伤员后送资源配置策略研究

参考国内外历史案例和数据,构建战场伤员产生的仿真模型。基于该模型,利用综合评价、资源配置优化算法,研究探讨连抢救组及营救护站的救治、后送运力配置及路径规划策略。利用假设战例验证模型,基于减员预计模型计算减员情况,分析了相应的营、连救治策略。结果验证一线伤员收拢后送运力配置及路径优化模型可靠,可为一线救治信息化、自动化、智能化发展提供技术支撑。本研究为一线伤员救治、收拢、后送力量配置及路径规划提供理论方法。     

Decision support system for mass dispensing of medications for infectious disease outbreaks and bioterrorist attacks

A simulation and decision support system, RealOpt^©, for planning large-scale emergency dispensing clinics to respond to biological threats and infectious disease outbreaks is described. The system allows public health administrators to investigate clinic design and staffing scenarios quickly. RealOpt^© incorporates efficient optimization technology seamlessly interfaced with a simulation module. The system's correctness and computational advantage are validated via comparisons against simulation runs of the same model developed on a commercial system. Simulation studies to explore facility layout and staffing scenarios for smallpox vaccination and for an actual anthrax-treatment dispensing exercise and post event analysis are presented. The system produces results consistent with the model built on the commercial system, but requires only a fraction of the computational time. Each smallpox scenario runs within 1 CPU minute on RealOpt^©, versus run times of over 5–10 h on the commercial system. The system's fast computational time enables its use in large-scale studies, in particular an anthrax response planning exercise involving a county with 864,000 households. The computational effort required for this exercise was roughly 30 min for all scenarios considered, demonstrating that RealOpt^© offers a very promising avenue for pursuing a comprehensive investigation involving a more diverse set of scenarios, and justifying work towards development of a robust system that can be widely deployed for use by state, local, and tribal health practitioners. Using our staff allocation and assignments for the Anthrax field exercise, DeKalb county achieved the highest throughput among all counties that simultaneously conducted the same scale of Anthrax exercise at various locations, with labor usage at or below the other counties. Indeed, DeKalb exceeded the targeted number of households, and it processed 50% more individuals compared to the second place county. None of the other counties achieved the targeted number of households. The external evaluators commented that DeKalb produced the most efficient floor plan (with no path crossing), the most cost-effective dispensing (lowest labor/throughput value), and the smoothest operations (shortest average wait time, average queue length, equalized utilization rate). The study proves that even without historical data, using our system one can plan ahead and be able to wisely estimate the required labor resources. The exercise also revealed many areas that need attention during the operations planning and design of dispensing centers. The type of disaster being confronted (e.g., biological attack, infectious disease outbreak, or a natural disaster) also dictates different design considerations with respect to the dispensing clinic, facility locations, dispensing and backup strategies, and level of security protection. Depending on the situation, backup plans will be different, and the level of security and military personnel, as well as the number of healthcare workers required, will vary. In summary, the study shows that a real-time decision support system is viable through careful design of a stand-alone simulator coupled with powerful tailor-designed optimization solvers. The flexibility of performing empirical tests quickly means the system is amenable for use in training and preparation, and for strategic planning before and during an emergency situation. The system facilitates analysis of “what-if'' scenarios, and serves as an invaluable tool for operational planning and dynamic on-the-fly reconfigurations of large-scale emergency dispensing clinics. It also allows for “virtual field exercises” to be performed on the decision support system, offering insight into operations flow and bottlenecks when mass dispensing is required for a region with a large population. The system, designed in modular form with a flexible implementation, enables future expansion and modification regarding emergency center design with respect to treatment for different biological threats or disease outbreaks. Working with emergency response departments, further fine-tuning and development of the system will be made to address different biological attacks and infectious disease outbreaks, and to ensure its practicality and usability.     

Agent-based modelling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies

This study investigates the effectiveness of simultaneous and staged evacuation strategies using agent-based simulation. In the simultaneous strategy, all residents are informed to evacuate simultaneously, whereas in the staged evacuation strategy, residents in different zones are organized to evacuate in an order based on different sequences of the zones within the affected area. This study uses an agent-based technique to model traffic flows at the level of individual vehicles and investigates the collective behaviours of evacuating vehicles. We conducted simulations using a microscopic simulation system called Paramics on three types of road network structures under different population densities. The three types of road network structures include a grid road structure, a ring road structure, and a real road structure from the City of San Marcos, Texas. Default rules in Paramics were used for trip generation, destination choice, and route choice. Simulation results indicate that (1) there is no evacuation strategy that can be considered as the best strategy across different road network structures, and the performance of the strategies depends on both road network structure and population density; (2) if the population density in the affected area is high and the underlying road network structure is a grid structure, then a staged evacuation strategy that alternates non-adjacent zones in the affected area is effective in reducing the overall evacuation time.     

INVESTIGATING THE VIABILITY OF SQUIRREL POPULATIONS; A MODELING APPROACH FOR THE ISLAND OF LESVOS,GREECE

ABSTRACT. Habitat loss and fragmentation are considered to be the most important factors responsible for population decreases in small mammal populations. Particularly important is also the effect of insularity that can act syn‐ergistically with the previous factors. Population Viability Analysis (PVA) combines the spatial component of the problem with the species population structure offering an integrated platform for testing and assessing the effects of critical parameters upon the population viability. Various management options can also be quantified and tested. In the case of Sciurus anomalous, a vulnerable squirrel species endemic in Lesvos, a series of threats and management problems were identified and assessed. A stochastic simulation model was developed and parameterized with field data for the species using the program Ramas/GIS. The results suggested that special attention has to be paid to the planning of road system networks and to stopping illegal hunting, especially when extinction risks for vulnerable populations are higher with the above threats.     

A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management

Hurricane forecasts are intended to convey information that is useful in helping individuals and organizations make decisions. For example, decisions include whether a mandatory evacuation should be issued, where emergency evacuation shelters should be located, and what are the appropriate quantities of emergency supplies that should be stockpiled at various locations. This paper incorporates one of the National Hurricane Center's official prediction models into a Bayesian decision framework to address complex decisions made in response to an observed tropical cyclone. The Bayesian decision process accounts for the trade-off between improving forecast accuracy and deteriorating cost efficiency (with respect to implementing a decision) as the storm evolves, which is characteristic of the above-mentioned decisions. The specific application addressed in this paper is a single-supplier, multi-retailer supply chain system in which demand at each retailer location is a random variable that is affected by the trajectory of an observed hurricane. The solution methodology is illustrated through numerical examples, and the benefit of the proposed approach compared to a traditional approach is discussed.     

人口密集场所紧急疏散问题的数学模型及其优化解

在人口密集场所(馆)观众席位区及疏散通道分布模拟图的基础上,着眼于紧急疏散方案制定中的主要问题,分析人群疏散过程中的主要矛盾,建立了属于非线性规划问题的人员紧急疏散的数学模型.在转化为整数线性规划问题后,可用分枝定界法求解,并用L ingo计算程序实现.所求得的最优解为布局比较简单的场馆制定紧急疏散方案提供了依据.