Minimize Evacuation Time Research Articles

Two-stage problems of optimal location and distribution of the humanitarian logistics system’s structural subdivisions

Purpose. To ensure the rational organization of the evacuation of people from a region affected by an emergency by developing a mathematical and algorithmic toolkit that will allow for the early distribution of transport and material resources, maximizing coverage of the affected areas while minimizing evacuation time. Methodology. System analysis of evacuation processes; mathematical modeling, the theory of continuous problems of optimal partitioning of sets, non-differentiable optimization. Findings. The object of the study is the two-stage evacuation logistic processes that occur when serving the population of areas affected by emergencies of a natural or technogenic nature. The research considers the possibility of optimally distributing human flows within the transportation system, the structural subdivisions of which are first-stage centers (first aid stations that carry out the reception of citizens from areas affected by the disaster) and second-stage centers (specialized units of the emergency aid system that provide further services to the evacuated population). The proposed mathematical model deals with the problem of optimally partitioning a continuous set with the placement of subset centers and additional connections. Methods for its solution have been described. We demonstrate the versatility of these models, as they can be used to describe logistic evacuation processes, organize assembly points, intermediate locations, evacuation reception points, and those providing primary assistance to the affected population. We calculate the appropriate number of essential products and deliver them from existing warehouses through distribution centers to the affected areas. Originality. As preventive measures to increase the level of population safety during an emergency, we consider the optimal placement of rescue facilities and the zoning of the territory to distribute evacuation traffic. We also address the problem of the optimal distribution of human flows in the transport and logistics system. Practical value. The presented models, methods, and algorithms enable the solution of many practical problems related to the development of preventive measures and the planning of rescue operations to ensure the population’s safety in case of emergencies. The theoretical results obtained are translated into specific recommendations that can be utilized when addressing logistical problems related to the organization of primary evacuation of the population from affected areas and their subsequent transportation to safer locations for further assistance.

Minmax regret for sink location on dynamic flow paths with general capacities

In dynamic flow networks, every vertex starts with items (flow) that need to be shipped to designated sinks. All edges have two associated quantities: length, the amount of time required for a particle to traverse the edge, and capacity, the number of units of flow that can enter the edge in unit time. The goal is to move all the flow to the sinks. A variation of the problem, modeling evacuation protocols, is to find the sink location(s) that minimize evacuation time, restricting the flow to be confluent. Solving this problem is NP-hard on general graphs, and thus research into optimal algorithms has traditionally been restricted to special graphs such as paths, and trees.A specialized version of robust optimization is minmax regret, in which the input flows at the vertices are only partially defined by constraints. The goal is to find a sink location that has the minimum regret over all the input flows that satisfy the partially defined constraints. Regret for a fully defined input flow and a sink is defined to be the difference between the evacuation time to that sink and the optimal evacuation time.A large recent literature derives polynomial time algorithms for the minmax regret k-sink location problem on paths and trees under the simplifying condition that all edges have the same (uniform) capacity. This paper develops an O(n4logn) time algorithm for the minmax regret 1-sink problem on paths with general (non-uniform) capacities. To the best of our knowledge, this is the first minmax regret result for dynamic flow problems in any type of graph with general capacities.

Mass Evacuation Transportation Model Using Hybrid Genetic Algorithm

The process of evacuating natural disasters requires careful planning. In particular, the evacuation process needs attention in the evacuation process because it involves the safety of many people. Evacuation time itself depends on information about incomplete evacuation routes such as those concerning desired velocity and obstacle parameters. When viewed in terms of transportation planning for evacuation, it is an Auto-Based Evacuation Model problem where the community, in this case, drivers, certainly do not know the evacuation planning or the route they will go through because, in the event of a disaster, it cannot be predicted which areas will be affected. The routing problem can be viewed as a discrete problem where the traffic problem is following a user equilibrium model. It has a bi-level structure. Top-level is used to minimize evacuation time using the contraflow strategy. At the same time, traffic volume and travel time are modeled at a low level. This problem is a linear programming problem whose solution will be optimized using a Hybrid Genetic Algorithm. This model is proposed to carry out mass evacuation processes based on time-window constraints. Finally, computational results are provided to demonstrate the validity and robustness of the proposed model. Based on the test results, it can be seen that the designed model can adjust the path that the vehicle follows with the vehicle station by adjusting the available capacity. The results showed that the intended route provided by the model was the shortest route.

Dynamic network flow location models and algorithms for quickest evacuation planning

Dynamic network flow problems have wide applications in evacuation planning. From a given subset of arcs in a directed network, choosing the suitable arcs for facility location with a given objective is very important in the optimization of flow in emergency cases. Because of the decrease in capacity of an arc by placing a facility in it, there may be a reduction in the maximum flow or increase in the quickest time. In this work, we consider a problem of identifying the optimal facility locations so that the increase in the quickest time is minimum. Introducing the quickest FlowLoc problem, we give strongly polynomial time algorithms to solve the single facility case. Realizing NP-hardness of the multi-facility case, we develop a mixed integer programming formulation of it and propose two polynomial time heuristics for its solution. Because of the growing concerns of arc reversals in evacuation planning, we introduce the quickest ContraFlowLoc problem and present exact algorithms to solve the single-facility case and heuristics to solve the multi-facility case, with polynomial time complexity. The solutions thus obtained here are practically important, particularly in evacuation planning, to systematize traffic flow with facility allocation minimizing evacuation time.

Development of fuzzy RUASP model - Grasp metaheuristics with time window: Case study of Mount Semeru eruption in East Java

Due to its geographical location, Indonesia is very vulnerable to the volcano eruption. Volcanic eruptions always bring impact to the surrounding community. To mitigate the negative effects, especially the impact on the safety of the population, disaster management is required. One of the concerns of disaster management is a proper allocation and scheduling of rescue teams to minimize evacuation time with expectations of saving as many lives as possible. For that purpose, the RUASP (Rescue Unit Assignment and Scheduling Problem) optimization model is developed to minimize a completion time of evacuation. The model considers the severity of damages and capability of the rescue team as well as safety time for the rescue team. There is a period for rescue teams to be able to perform their duties safely and fuzzy time on the fields. Physical limitations and device limitations are the inhibiting factors for evacuation activities during low light conditions. We also developed a GRASP Metaheuristics algorithm for solving the proposed RUASP model. To test the model we use a certain historical data. The completion time of the proposed model is 21.92% faster than the computation time of the previous model, 12.56 seconds.

The Optimization for Location of Building Evacuation Exits Considering the Uncertainty of Occupant Density Using Polynomial Chaos Expansion and Genetic Algorithm

Abstract In prescriptive fire protection designs of buildings, exit location is generally designed with the constraint of the maximum travel distance. And the optimal exit location has not been given enough attention to in performance-based fire protection designs of buildings. However, in order to improve the reliability of successful evacuation, the optimal exit location for minimizing evacuation time should be studied with consideration of the uncertainty of initial occupant density. Due to the expensive computational cost, the surrogate-based optimization is proposed to search the optimal exit location, which combines the polynomial chaos expansion and genetic algorithm. The polynomial chaos expansion is used to construct the surrogate model of evacuation time and then genetic algorithm is applied to the polynomial chaos expansion of evacuation time to search the optimal exit location. In order to demonstrate the proposed method, a fire compartment of commercial buildings with two exits is presented. The results of this case study suggest that the optimal layout of two exits with the same size should be distributed symmetrically and the optimal exit location is different for different probability levels. When the probability level of successful evacuation is low with two narrow exits, the better method is merging two exits into be one exit around the center of the wall, which is also consistent with that determined by minimizing the maximum travel distance. However, when the probability level of successful evacuation is high with two narrow exits, the optimal location of two exits should be around two corners of the wall in this case. This proposed method can be used to find the suitable exit location under uncertain initial occupant density, which provides a reference for the performance-based design of building exits.

Multiple exits evacuation algorithm for real-time evacuation guidance

Most studies for minimizing total evacuation time do not take into account aspects of realistic evacuation guidance because they focus on minimizing evacuation time arithmetically. In the mentioned study, occupants in one space can be divided and move to different exits in order to minimize the evacuation time. However, in an emergency situation, it is practically difficult to guide occupants in a space to different directions, and may confuse them significantly. For this reason, this study proposed a multiple exits evacuation algorithm (MEEA) that guide the occupants in one space to the same exit. The MEEA is based on graph theory and computes a process of exits assignment of the nodes, leading to the division of the spaces based on the exits. Each exit competitively absorbs nodes, repeating until evacuation times of exits are balanced and the total evacuation time is minimized. In order to verify MEEA, this study used evacuation simulators based on cellular automata called EgresSIM to compare the evacuation results of well-known evacuation models EVACNET4 and MEEA.

综合楼宇火灾疏散路线研究

利用科学有效的方法规划应急疏散路线，对提高综合楼宇内的应急效果、提高救援速度和减小灾害损失具有重要作用。综合楼宇是火灾易发区，在火灾发生时，楼内布局和设施的布置可能使疏散能力降低，应急出口的分配和疏散路线的规划是逃生和救援的关键因素。本文着重研究了综合楼宇应急疏散路线的规划方法，推导出算法，并在实际案例中进行应用验证，利用应急疏散空间网络模型和性能变量，结合应急疏散路线的最优化及动态模拟分析，构建出疏散时间最小化为目标的疏散路线。此方法可运用在大多数综合楼宇的火灾疏散应用中，为其他综合楼宇的应急疏散应用提供参考借鉴。 Scientifically and effectively planning emergency evacuation routes has an important role in en-hancing emergency response, improving rescue speed and reducing disaster losses in complex buildings. Complex building is a fire prone area. In the case of fire, the layout and facilities layout may reduce the evacuation capacity, and the distribution of emergency exits and evacuation routes planning are the key factors for escape and rescue. This paper focuses on the comprehensive building emergency evacuation route planning method, and applied and verified in the actual case. Using evacuation space network model and performance variables, combined with the optimization of emergency evacuation routes and dynamic simulation analysis, evacuation routes with the goal of minimizing evacuation time are constructed. This method can be used as a reference for emergency evacuation of other complex buildings.

Optimal Path Planning With Spatial-Temporal Mobility Modeling for Individual-Based Emergency Guiding

This paper proposes an individual-based framework for emergency guiding. The spatial-temporal mobility of all people is modeled to determine a dedicated path that provides the shortest evacuation time for each person. According to our review of relevant research, this is the first optimal solution without using time-expanded graphs, and corridor capacities and lengths, exit capacities, concurrent motion, and distribution of people are considered to minimize evacuation time. We prove that the proposed path planning algorithm is optimal and analyze its time and space complexity. The proposed framework can be used to estimate the evacuation time for each person accurately and evenly distribute evacuation load among exits to achieve the most efficient load balance. In the proposed framework, the congestion in all corridors and exits can be alleviated to maximally reduce the total evacuation time. Simulation results show that our approach outperforms existing schemes, and can be used to determine an optimal escape path for each person and, thus, achieve the shortest total evacuation time.

Minimal Evacuation Times and Stability

We consider a system where packets (jobs) arrive for processing using one of the policies in a given class. We study the connection between the minimal evacuation time and the stability region of the system and show that evacuation time optimal policies can be used for stabilizing the system (and for characterizing its stability region) under broad assumptions. Conversely, we show that while a stabilizing policy can be suboptimal in terms of evacuation time, one can always design a randomized version of any stabilizing policy that achieves an optimal evacuation time in the asymptotic regime when the number of evacuated packets scales to infinity.

Dynamic Wireless Network Coding With Overhearing and Variable Channel Rates

We study a one-hop broadcast channel with two receivers. The receivers have side information obtained by overhearing wireless channels. The relay takes control decisions by coding transmissions based on its knowledge of side information in the receivers. We consider two control mechanisms. In the ACK system, the relay has definite knowledge of side information announced via overhearing reports. In the NACK system, the relay has statistical knowledge of side information and receives feedback after every decoding failure. Our contribution is as follows. We provide the minimal evacuation times for the two systems and obtain analytical expressions of the throughput region for the ACK and the code-constrained region for the NACK system. When the transmission rates are the same (r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> = r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) or when the receiver with the highest transmission rate has perfect side information (p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> =1), we show that the two regions are equal. We then provide simple joint xor coding and scheduling policies that achieve those regions and, thus, are throughput optimal. Subsequently, we evaluate the report overhead performance for both mechanisms and reflect on the involved tradeoff with throughput. Ultimately, we demonstrate by simulations that the proposed throughput optimal policies can be appropriately enhanced to have good delay properties, particularly for protocols that utilize sequenced packet delivery.

Optimal Critical Infrastructure Retrofitting Model for Evacuation Planning

In emergency situations, it is necessary to safely evacuate the population in order to save lives. The road network infrastructure is vulnerable for extreme events, and as a result its ability to supply the required capacity can be seriously hampered. Hence, it is crucial to identify those critical segments which prohibit safe evacuation, and find an optimal retrofit scheme at the network level in order to minimize evacuation time. This work introduces an emergency evacuation model that considers infrastructures vulnerability, event location and magnitude, road network, transportation demand and evacuation areas in order to identify the critical infrastructures and recommend budget allocation for increasing network capacity for minimizing evacuation time, given budget alternatives. The infrastructures’ analysis was based on the knowledge about mechanics characteristics of a set of bridges, and about a set of possible seismic scenarios related to the area of interest. By using fragility curves of bridges, the damage state of them has been assessed. By making a series of hypotheses on how a bridge damage state can influence links’ functionality, reduced capacity was assigned to the road network. The result is the estimation of the retrofit cost needed for a specific seismic scenario, considering the most effective retrofit intervention type, previously identified for each bridge. The infrastructures’ analysis results were used by the evacuation model for optimal budget allocation of retrofits strategies in order to attain a desired evacuation time frame. The procedure has been applied to an urban network in north Italy.

Floor Field Model Based on Cellular Automata for Simulating Indoor Pedestrian Evacuation

A new static floor field method for simulations of evacuation processes based on cellular automaton was presented in this paper. This model applies an inertia static floor field approach to describe the interaction between the pedestrians and the cell. Here we study a rather simple situation and a complex scenario. We simulate and reproduce Seyfried’s field experiments at the Research Centre Jülich and use its empirical data to validate our model. The concept of scenario-familiarity of the crowd has been proposed to explain the model. It is shown that the variation of the model parameters deeply impacts the evacuation efficiency. The relation between minimal evacuation times and the knowledge of the exit that the pedestrian acknowledges is discussed.

Modeling of building evacuation using ladders

Existing research and tools used for building evacuation planning do not take into account the common practice of using ladders for rescue operations. The ladders provide a simple and practical way of creating additional exits with a potential to significantly reduce the evacuation time. Use of ladders is critical in case of severe disasters and when some normal exits get blocked. To our knowledge, this paper presents the first systematic planning approach for optimal placement of a limited number of available ladders. We first propose modifications to the existing models of buildings to incorporate ladders and ladder points (locations in the building where ladders can be placed). Next, we develop optimization formulations to solve the following evacuation planning problems when a limited number of ladders are available: (i) optimal deployment of a given number of ladders to minimize evacuation time and (ii) finding minimum number of ladders along with their locations necessary to evacuate a building in a given evacuation time. These problems, posed as integer linear programming formulations, are applied to two case studies to demonstrate the importance of using ladders. The results show that evacuation plans can be significantly improved by optimally placing ladders at the selected ladder points.

Forecasting model for pedestrian distribution under emergency evacuation

Pedestrian distribution forecasting on the road network is developed to support the evacuation decision-making. The numbers of evacuees distributed on each road link are stochastic, uncertain and multi-dependent. Therefore, a Gaussian Bayesian networks (GBN) based forecasting model is presented, considering the pedestrian flow characteristics, optimization of evacuation route and evacuation decision-making. In the forecasting model, the route choice probabilities obtained by minimizing evacuation time are applied to correct the regression coefficients of GBN. Finally, an example is provided to illustrate the usefulness of this model. Research shows that this model not only reflects the complexity and dynamics of evacuation process but also performs an accurate forecasting on the time development of the pedestrian distributed in the evacuation space.

Contraflow Transportation Network Reconfiguration for Evacuation Route Planning

Given a transportation network having source nodes with evacuees and destination nodes, we want to find a contraflow network configuration, i.e., ideal direction for each edge, to minimize evacuation time. Contraflow is considered a potential remedy to reduce congestion during evacuations in the context of homeland security and natural disasters (e.g., hurricanes). This problem is computationally challenging because of the very large search space and the expensive calculation of evacuation time on a given network. To our knowledge, this paper presents the first macroscopic approaches for the solution of contraflow network reconfiguration incorporating road capacity constraints, multiple sources, congestion factor, and scalability. We formally define the contraflow problem based on graph theory and provide a framework of computational workload to classify our approaches. A greedy heuristic is designed to produce high quality solutions with significant performance. A bottleneck relief heuristic is developed to deal with large numbers of evacuees. We evaluate the proposed approaches both analytically and experimentally using real world datasets. Experimental results show that our contraflow approaches can reduce evacuation time by 40% or more.

Fluid resuscitation strategies in the Israeli army.

Medical training in the Israel Defense Forces (IDF) is currently based on the principles of the Advanced Trauma Life Support course of the American College of Surgeons termed Military Trauma Life Support. The Advanced Trauma Life Support guidelines provide a systematic standardized approach to the treatment of trauma casualties that has been very successful in civilian trauma. On the battlefield, however, these guidelines have been modified according to the combat environment. The factors that influence these changes are tactical considerations, availability and level of training of medical personal, direct enemy fire, medical equipment limitations, means of transportation of casualties, and the variable transportation time from the front line to the first medical echelon. The basic strategy of the IDF is to bring the military physician or paramedic and airlifted surgical units as close as possible to the front line, to minimize evacuation time. Also, evacuation helicopters that land in the combat zone close to the front line, sometimes under direct fire, usually have a military physician on board. The dilemma of "scoop and run" or "stay and stabilize" in hemorrhagic shock has been solved in the IDF toward early rapid evacuation of casualties to a surgical unit. Immediately after airway and breathing have been secured, if evacuation time is less than 1 hour, the intravenous line and fluid resuscitation is started en route to the medical facility. When evacuation time is longer than 1 hour, an intravenous line is always started before evacuation. In controlled hemorrhagic shock, where the source of bleeding has been controlled and evacuation time is less than 1 hour, fluid resuscitation with lactated Ringer's solution or normal saline is started, to achieve normalization of hemodynamic parameters. When evacuation time exceeds 60 minutes, colloids such as Hemaccel or hydroxyethyl starch are added. In uncontrolled hemorrhagic shock, where internal bleeding has temporarily stopped because of hypotension, vasoconstriction, and thrombus formation, aggressive fluid resuscitation with lactated Ringer's solution to achieve normal hemodynamic parameters is prohibited, because it may induce internal rebleeding and hemodynamic decompensation. When evacuation time exceeds 60 minutes, the use of crystalloids and colloids is indicated. If brain injury is suspected, fluid resuscitation should be aimed toward normalization of hemodynamic parameters.

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

We present simulations of evacuation processes using a recently introduced cellular automaton model for pedestrian dynamics. This model applies a bionics approach to describe the interaction between the pedestrians using ideas from chemotaxis. Here we study a rather simple situation, namely the evacuation from a large room with one or two doors. It is shown that the variation of the model parameters allows to describe different types of behaviour, from regular to panic. We find a non-monotonic dependence of the evacuation times on the coupling constants. These times depend on the strength of the herding behaviour, with minimal evacuation times for some intermediate values of the couplings, i.e., a proper combination of herding and use of knowledge about the shortest way to the exit.