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.     

营救设备数量受限的应急疏散模型和算法

考虑在实际中可能面临着某些救援活动,必须借助于营救设备或者依赖营救人员的引导才能得以完成．针对这种情况,给出了设备数量受限的应急疏散模型．由于目标函数是疏散时间最小化,在考虑路径容量限制时,首先通过优先饱和最短路径来确定可行路径集合,把可行路径集合中的k短路作为初始解,再以每条路径上流量与旅行时间的比值流速作为更新路径的准则,每步迭代通过保留流速较大的路径来保存当前疏散时间最小的路径集合,从而确定疏散方案．最后通过算例验证了该算法的有效性和可行性．     

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.     

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.     

The Safest Escape problem

In this paper, the Safest Escape (SEscape) problem is defined for providing evacuation plans for emergency egress from large buildings or a geographical region. The objective of the SEscape problem is to determine the set of paths and number of evacuees to send along each path such that the minimum probability of arrival at an exit for any evacuee is maximized. Such paths minimize the risk incurred by the evacuees who are forced to take the greatest risk. The problem is considered in a dynamic and time-varying network, where arc capacities are recaptured over time, arc traversal times are time-varying and arc capacities are random variables with probability distribution functions that vary with time. An exact algorithm, the SEscape algorithm, is proposed to address this problem.     

Integrating simulation modelling and GIS: spatial decision support systems for evacuation planning

A prototype spatial decision support system (SDSS) has been designed for contingency planning for emergency evacuations which combines simulation techniques with spatial data handling and display capabilities of a geographical information system (GIS). It links together the topographical support and analysis provided by the GIS–ARC/INFO, with a simulation model designed to simulate the dynamics of an evacuation process in detail. Our aim has been to design a SDSS so that it provides an interactive evacuation simulator with dynamic graphics that allows for experimentation with policies by providing rapid feedback from the simulation. The idea is that emergency planners will be able to use the SDSS to experiment with emergency evacuation plans in order to plan for different contingencies. This paper concentrates on the issues involved in designing an effective integration link interface between the GIS and the simulation model when building a SDSS of this type.     

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。     

无预警紧急疏散中公交车辆路径的确定方法

针对无预警式紧急疏散中公交救援车辆的最佳路径确定问题,提出了一个非线性混合整数规划模型.模型不仅考虑了有接收能力限制的多避难所系统,还对如何处理具有不同载客上限的公交救援车进行了分析.利用添加了虚拟路段和节点的时空网络,在以加权的综合疏散时间最小为目标的同时实现了疏散伤亡最小化.通过分析实际疏散的实施过程,得到了一种产生模型可行解的有效方法.通过将时间滚动式的流量加载模式与经典遗传算法相结合,给出了新模型的实用解法.最后,通过算例验证了模型和算法的有效性.     

An Algorithm for Solving Multicriterion Linear Programming Problems with Examples

The purpose of this paper is to develop a useful technique for solving linear programmes involving more than one objective function. Motivation for solving multicriterion linear programmes is given along with the inherent difficulty associated with obtaining a satisfactory solution set. By applying a linear programming approach for the solution of two person–zero sum games with mixed strategies, it is shown that a linear optimization problem with multiple objective functions can be formulated in this fashion in order to obtain a solution set satisfying all the requirements for an efficient solution of the problem. The solution method is then refined to take into account disparities between the magnitude of the values generated by each of the objective functions and solution preferences as determined by a decision-maker. A summary of the technique is then given along with several examples in order to demonstrate its applicability.     

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。     

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.     

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.     

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     

An Interactive Method as an Aid in Solving Bicriterion Mathematical Programming Problems

In this paper, a man-machine interactive method is presented as an aid in solving the bicriterion mathematical programming problem. It is assumed that the two objective functions are real-valued functions of the decision variables which are themselves constrained to some compact and nonempty set. The overall utility function is assumed to be unknown explicitly to the decision-maker but is assumed to be a real-valued function defined on the pairs of feasible values of the objective functions and monotone non-decreasing in each argument. The decision-maker is required only to provide yes or no answers to questions regarding the desirability of increase or decrease in objective function values of solutions that he will not accept as optimal. Convergence of the method is indicated and a numerical example is presented in order to demonstrate its applicability.     

紧急网络中的最小饱和流问题

网络N中的一个流,如果沿前向已无法再增流,则称为饱和流,在交通拥挤或紧急疏散时,网络往往被一饱和流所堵塞。显然,这饱和流的值越小,网络的性能就越差。于是从网络分析的观点就提出最小饱和流问题。本文首先证明此问题NP－困难的。然后给出关于最小饱和流与最大流的关系及算法方面的结果。     

An interactive method as an aid in solving multi-objective mathematical programming problems

In this paper, an interactive method is presented as an aid in solving multi-objective programming problems. It is assumed that the m objective functions are real-valued functions of the decision variables which are themselves constrained to some compact and nonempty set. The overall utility function is assumed to be unknown explicitly to the decision-maker but is assumed to be a real-valued, unimodal function defined on the m-tuples of feasible values of the objective functions and monotone nondecreasing in each argument. The decision-maker is required only to provide yes or no answers to questions regarding the desirability of increase or decrease in objective function values of solutions that he will not accept as optimal. Convergence of the method is indicated and a numerical example is presented in order to demonstrate its applicability.     

A taxonomy for emergency service station location problem

The emergency service station (ESS) location problem has been widely studied in the literature since 1970s. There has been a growing interest in the subject especially after 1990s. Various models with different objective functions and constraints have been proposed in the academic literature and efficient solution techniques have been developed to provide good solutions in reasonable times. However, there is not any study that systematically classifies different problem types and methodologies to address them. This paper presents a taxonomic framework for the ESS location problem using an operations research perspective. In this framework, we basically consider the type of the emergency, the objective function, constraints, model assumptions, modeling, and solution techniques. We also analyze a variety of papers related to the literature in order to demonstrate the effectiveness of the taxonomy and to get insights for possible research directions.     

基于成本效益分析的救护车多时段布局优化研究

院前急救服务水平和救护资源之间存在悖反效益,本文综合考虑急救服务效果与急救网络成本,应用延误成本刻画急救效果,运营成本刻画急救资源使用,同时考虑需求规模、需求空间分布、救护车行驶速度以及救护车不可获得率随时间变化的影响,建立以最小化社会总成本为目标的救护车多时段布局优化模型,应用上海市松江区的实际数据,系统研究多时段救护车布局优化问题。计算结果表明优化后的系统在保证80%的高标准覆盖水平下,社会总成本比原系统下降32.23%。相比静态的情况,考虑时变因素可以使社会总成本下降15.8%,双覆盖率提高12.84%,各时段车辆繁忙率方差下降91.67%。