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．     

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.     

Optimal egress time calculation and path generation for large evacuation networks

Finding the optimal clearance time and deciding the path and schedule of evacuation for large networks have traditionally been computationally intensive. In this paper, we propose a new method for finding the solution for this dynamic network flow problem with considerably lower computation time. Using a three phase solution method, we provide solutions for required clearance time for complete evacuation, minimum number of evacuation paths required for evacuation in least possible time and the starting schedules on those paths. First, a lower bound on the clearance time is calculated using minimum cost dynamic network flow model on a modified network graph representing the transportation network. Next, a solution pool of feasible paths between all O-D pairs is generated. Using the input from the first two models, a flow assignment model is developed to select the best paths from the pool and assign flow and decide schedule for evacuation with lowest clearance time possible. All the proposed models are mixed integer linear programing models and formulation is done for System Optimum (SO) scenario where the emphasis is on complete network evacuation in minimum possible clearance time without any preset priority. We demonstrate that the model can handle large size networks with low computation time. A numerical example illustrates the applicability and effectiveness of the proposed approach for evacuation.     

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。     

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.     

Aggregate-level demand management in evacuation planning

Without successful large-scale regional evacuations, threats such as hurricanes and wild-fires can cause a large loss of life. In this context, automobiles are oftentimes an essential transportation mode for evacuations, but the ensuing traffic typically overwhelms the roadway capacity and causes congestion on a massive scale. Congestion leads to many problems including longer, costlier, and more stressful evacuations, lower compliance rates, and increased risk to the population. Supply-based strategies have traditionally been used in evacuation planning, but they have been proven to be insufficient to reduce congestion to acceptable levels. In this paper, we study the demand-based strategies of aggregate-level staging and routing to structure the evacuation demand, both with and without congestion. We provide a novel modeling framework that offers strategic flexibility and utilizes a lexicographic objective function that represents a hierarchy of relevant evacuation-based goals. We also provide insights into the nature and effect of network bottlenecks. We compare our model with and without congestion in relation to tractability, normative optimality, and robustness under demand uncertainty. We also show the effectiveness of using demand-based strategies as opposed to using the status quo that involves a non-staged or simultaneous evacuation process. Effective solution procedures are developed and tested using hypothetical problem instances as well as using a larger study based on a portion of coastal Virginia, USA.     

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.     

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.     

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。     

Efficient contraflow algorithms for quickest evacuation planning

The optimization models and algorithms with their implementations on flow over time problems have been an emerging field of research because of largely increasing human-created and natural disasters worldwide. For an optimal use of transportation network to shift affected people and normalize the disastrous situation as quickly and Efficiently as possible, contraflow configuration is one of the highly applicable operations research (OR) models. It increases the outbound road capacities by reversing the direction of arcs towards the safe destinations that not only minimize the congestion and increase the flow but also decrease the evacuation time significantly. In this paper, we sketch the state of quickest flow solutions and solve the quickest contraflow problem with constant transit times on arcs proving that the problem can be solved in strongly polynomial time O(nm²(log n)²), where n and m are number of nodes and number of arcs, respectively in the network. This contraflow solution has the same computational time bound as that of the best min-cost flow solution. Moreover, we also introduce the contraflow approach with load dependent transit times on arcs and present an Efficient algorithm to solve the quickest contraflow problem approximately. Supporting the claim, our computational experiments on Kathmandu road network and on randomly generated instances perform very well matching the theoretical results. For sufficiently large number of evacuees, about double flow can be shifted with the same evacuation time and about half time is sufficient to push the given flow value with contraflow reconfiguration.     

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.     

Resource allocation in state-dependent emergency evacuation networks

Most of the previous studies on the Emergency Evacuation Problem (EEP) assume that the length and widths of the circulation spaces are fixed. This assumption is only true if one is evaluating facilities that are already built. However, when designing the network for the first time, the size of the circulation space is not known to the designer, in fact it is one of several design parameters. After the routes have been established, it seems that the next logical question is to find out whether or not the system circulation spaces are capable of accommodating the traffic for both normal circulation and in an emergency. The problem of designing emergency evacuation networks is very complex and it is only recently that queueing networks are now being used to model this problem. Recent advances include state-dependent queueing network models that incorporate the mean value analysis algorithm to capture the non-linearities in the problem. We extend these models by incorporating the mean value analysis algorithm within Powell's derivative free unconstrained optimization algorithm. The effect of varying circulation widths on throughput will be discussed and a methodology for solving the resource allocation problem is proposed and demonstrated on several examples. The computational experience of the new methodology illustrates its usefulness in network design problems.     

Flow location (FlowLoc) problems: dynamic network flows and location models for evacuation planning

In this paper we combine two modeling tools to predict and evaluate evacuation plans: (dynamic) network flows and locational analysis. We present three exact algorithms to solve the single facility version 1-FlowLoc of this problem and compare their running times. After proving the $\mathcal{NP}$ -completeness of the multi facility q-FlowLoc problem, a mixed integer programming formulation and a heuristic for q-FlowLoc are proposed. The paper is concluded by discussing some generalizations of the FlowLoc problem, such as the multi-terminal problem, interdiction problem, the parametric problem and the generalization of the FlowLoc problem to matroids.     

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.     

An efficient algorithm for the evacuation problem in a certain class of networks with uniform path-lengths

In this paper, we consider the evacuation problem in a network which consists of a directed graph with capacities and transit times on its arcs. This problem can be solved by the algorithm of Hoppe and Tardos [B. Hoppe, É. Tardos, The quickest transshipment problem, Math. Oper. Res. 25(1) (2000) 36–62] in polynomial time. However their running time is high-order polynomial, and hence is not practical in general. Thus, it is necessary to devise a faster algorithm for a tractable and practically useful subclass of this problem. In this paper, we consider a network with a sink s such that (i) for each vertex v≠s the sum of the transit times of arcs on any path from v to s takes the same value, and (ii) for each vertex v≠s the minimum v-s cut is determined by the arcs incident to s whose tails are reachable from v. This class of networks is a generalization of grid networks studied in the paper [N. Kamiyama, N. Katoh, A. Takizawa, An efficient algorithm for evacuation problem in dynamic network flows with uniform arc capacity, IEICE Trans. Infrom. Syst. E89-D (8) (2006) 2372–2379]. We propose an efficient algorithm for this network problem.     

Simultaneous evacuation and entrance planning in complex building based on dynamic network flows

This paper presents mathematical models and a heuristic algorithm that address a simultaneous evacuation and entrance planning. For the simultaneous evacuation and entrance planning, four types of mathematical models based on the discrete time dynamic network flow model are developed to provide the optimal routes for evacuees and responders within a critical timeframe. The optimal routes obtained by the mathematical models can minimize the densification of evacuees and responders into specific areas. However, the mathematical model has a weakness in terms of long computation time for the large-size problem. To overcome the limitation, we developed a heuristic algorithm. We also analyzed the characteristics of each model and the heuristic algorithm by conducting case studies. This study pioneers area related to evacuation planning by developing and analyzing four types of mathematical models and a heuristic algorithm which take into account simultaneous evacuation and entrance planning.     

Ranking robustness and its application to evacuation planning

We present a new approach to handle uncertain combinatorial optimization problems that uses solution ranking procedures to determine the degree of robustness of a solution. Unlike classic concepts for robust optimization, our approach is not purely based on absolute quantitative performance, but also includes qualitative aspects that are of major importance for the decision maker.We discuss the two variants, solution ranking and objective ranking robustness, in more detail, presenting problem complexities and solution approaches. Using an uncertain shortest path problem as a computational example, the potential of our approach is demonstrated in the context of evacuation planning due to river flooding.     

需求不确定条件下社区应急疏散协作调度优化模型

质量安全、自然灾害、公共卫生等突发事件社区应急疏散中的灾民数量具有不确定性,但目前的研究很少关注多种运输方式协作的应急疏散中灾民数量的不确定性。针对灾民数量的不确定性,以疏散灾民数量最大化,以及疏散成本最小化作为优化目标,,该文构建了多种运输方式协作的社区应急疏散模糊机会约束规划模型。在模型求解时,论文使用自适应遗传算子对多目标遗传算法进行改进,以提高算法优化效率。最后,论文使用算例对提出的模型进行验证,证明了该模型和方法可以有效完成需求不确定条件下的社区应急疏散协作调度优化工作。     

Multi-objective evacuation routing in transportation networks

In this paper, the optimal design and analysis of evacuation routes in transportation networks is examined. An methodology for optimal egress route assignment is suggested. An integer programming (IP) formulation for optimal route assignment is presented, which utilizes M/G/c/c state dependent queueing models to cope with congestion and time delays on road links. M/G/c/c simulation software is used to evaluate performance measures of the evacuation plan: clearance time, total travelled distance and blocking probabilities. Extensive experimental results are included.     

On Solving Quickest Time Problems in Time-Dependent, Dynamic Networks

In this paper, a pseudopolynomial time algorithm is presented for solving the integral time-dependent quickest flow problem (TDQFP) and its multiple source and sink counterparts: the time-dependent evacuation and quickest transshipment problems. A more widely known, though less general version, is the quickest flow problem (QFP). The QFP has historically been defined on a dynamic network, where time is divided into discrete units, flow moves through the network over time, travel times determine how long each unit of flow spends traversing an arc, and capacities restrict the rate of flow on an arc. The goal of the QFP is to determine the paths along which to send a given supply from a single source to a single sink such that the last unit of flow arrives at the sink in the minimum time. The main contribution of this paper is the time-dependent quickest flow (TDQFP) algorithm which solves the TDQFP, i.e. it solves the integral QFP, as defined above, on a time-dependent dynamic network, where the arc travel times, arc and node capacities, and supply at the source vary with time. Furthermore, this algorithm solves the time-dependent minimum time dynamic flow problem, whose objective is to determine the paths that lead to the minimum total time spent completing all shipments from source to sink. An optimal solution to the latter problem is guaranteed to be optimal for the TDQFP. By adding a small number of nodes and arcs to the existing network, we show how the algorithm can be used to solve both the time-dependent evacuation and the time-dependent quickest transshipment problems. This revised version was published online in August 2006 with corrections to the Cover Date.