Optimal Evacuation Research Articles

Best Repairing Algorithm for Transportation Lifeline Network under Major Natural Disasters

To repair remote mountainous transportation lifeline networks destructed by major natural disasters, a best repair algorithm developed from augmented variational method (AVM) is presented. By constructing a residual network of the original network, augmenting a given feasible flow along the augmented path and introducing pre-flow push algorithm, the optimal evacuation way in the remaining paths is amended and found out. Finally, the calculating process of pre-flow push algorithm was illustrated through a case study. According to actual situation of the road, measures for repairing the lifeline network were proposed. Result of the case study shows that the ability to transfer road traffic after secondary accidents will be improved by calculating and comparing the modified values of AVM to the critical sections in remote areas.

Load’s Damping Swing by Trolley’s Driving Force Control for Overhead or Gantry Crane

In order to obtain the trolley-load system’s dynamic equations for overhead crane or gantry crane, analyzed the dynamic system and deduced the transfer function between the load’s sway angle and the force acting on the trolley from dynamic equations. The force control mode for load’s damping swing is an effective measure of compensation for active anti-swing. Dynamic simulation results show that the optimal evacuation time of the force acting on the trolley is a key parameter that affects the damping swing’s effect. The load’s damping swing effect is favorable when the driving force is withdrawn at optimal withdrawing time; the load’s swing angle’s amplitude will increase with driving force’s increase, but the damping swing effect is still favorable if the optimal withdrawing time is favorably controlled.

Implementing real-time grouping for fast egress in emergency

Mass events such as the Olympic games or popular entertainment gathering often attract hundreds of thousands of people. If an abrupt event (e.g., fire, bomb threat) prompts people to rush to exits, stampedes may occur, creating secondary damages. Thus quickly dispersing crowd population to safe places in the least time while managing to avoid congestion and/or stampede is an important task with the occurrence of such events. This study presents an optimal evacuation model to meet this goal. By identifying some key themes that contribute to crowd disasters, the model implements a real-time concurrent grouping to ensure at-risk people are guided to safe places in the least time. The underlying rationale of the strategy is to advocate that competition should be replaced with coherence, and people should coordinate and collaborate to move out in an orderly way through scientifically using multiple routes. In doing so, each person receives an equal opportunity to exit the incident site, and the general effectiveness of performing an evacuation is achieved to an optimal level. To verify the proposed method, we conduct a simulation in which we compare our method with two benchmark cases: random self-evacuation and herding behavior. The results demonstrate that the proposed strategy can rescue people at risk much faster and more safely than two benchmark cases. We implement the proposed model through a web-based wireless decision support system, which provides a useful tool to both first responders and people affected for time-based crowd management in response to an ongoing crowd incident.

The usability of selected base maps for crises management—users' perspectives

Cartography has become an important tool for supporting decision-making processes in the field of crisis management. Maps (or GIS) can be used for solving various problems, e.g. the localization of accident site, the delimitation of endangered areas, the formulation of evacuation plans and others. People involved in decision-making processes use various procedures to solve these problems. However, a suitable and efficient form of cartographic support for particular situations and crisis management cycle stages is still missing. The main goal of the experiment was twofold. First, we wanted to assess the interdisciplinary (cartography–psychology) web-based testing environment and achieve the first usability results. Second, the use of different cartographic base map representations was analysed in order to judge the efficiency for specific situations. Testing was focused on various types of tasks, e.g. simple sign selection, the possibility of memorizing important information from the map and the choice of the optimal evacuation route. The overall testing was performed within the interactive web environment, based on predefined templates, automatically recorded and calibrated against the evaluation of the pretest users’ abilities. Preliminary testing results provide valuable inputs concerning the usability of selected base maps for supporting decision-making processes during various crisis situations.

Hierarchical multi-objective evacuation routing in stadium using ant colony optimization approach

Evacuation planning is a fundamental requirement to ensure that most people can be evacuated to a safe area when a natural accident or an intentional act happens in a stadium environment. The central challenge in evacuation planning is to determine the optimum evacuation routing to safe areas. We describe the evacuation network within a stadium as a hierarchical directed network. We propose a multi-objective optimization approach to solve the evacuation routing problem on the basis of this hierarchical directed network. This problem involves three objectives that need to be achieved simultaneously, such as minimization of total evacuation time, minimization of total evacuation distance and minimal cumulative congestion degrees in an evacuation process. To solve this problem, we designed a modified ant colony optimization (ACO) algorithm, implemented it in the MATLAB software environment, and tested it using a stadium at the Wuhan Sports Center in China. We demonstrate that the algorithm can solve the problem, and has a better evacuation performance in terms of organizing evacuees’ space–time paths than the ACO algorithm, the kth shortest path algorithm and the second generation of non-dominated sorting genetic algorithm were used to improve the results from the kth shortest path algorithm.

Managing Large-Scale Multimodal Emergency Evacuations

This article presents the development of a novel framework that optimizes the evacuation of large cities using multiple modes including vehicular traffic, rapid transit, and mass-transit shuttle buses. A large-scale evacuation model is developed for the evacuation of the City of Toronto in case of emergency. A demand estimation model is first designed to accurately quantify the evacuation demand by mode (drivers vs. transit users), over time of the day when the crisis begins, and over space (location). The output of the demand estimation model is then fed into two optimization platforms: (1) an optimal spatio-temporal evacuation (OSTE) model that synergizes evacuation scheduling, route choice, and destination choice for vehicular traffic and (2) a model based on a new variant of the vehicle routing problem to optimize the routing and scheduling of mass-transit vehicles. The study concluded that OSTE can clear the City of Toronto 4 times faster than the do-nothing strategy. The OSTE average automobile evacuation time for the 1.21 million people using their cars is close to 2 h. The optimization of the routing and scheduling of the readily available Toronto Transit Commission fleet (4 Rapid Transit lines and 1320 transit buses used as shuttles) can efficiently evacuate the transit-dependent population (1.34 million) within 2 h.

A Hybrid Bilevel Model for the Optimal Shelter Assignment in Emergency Evacuations

: The rise in natural and man-made disasters in recent years has led to an increased interest in emergency evacuation planning. Athough the vast majority of the existing evacuation planning models assumes system optimal (cooperative) behavior, recent research has shown that during large evacuations people tend to exhibit selfish (noncooperative) behavior. This article presents a hybrid bilevel model that balances both behavioral assumptions (in the upper level, shelter assignment occurs in a system optimal fashion, whereas evacuees are free to choose how to reach their assigned shelters in the lower level), hence providing a model that is more in line with the current state-of-the-knowledge of human behavior during disasters. The proposed model is solved using a simulated annealing algorithm. A hypothetical evacuation scenario in Sioux Falls, South Dakota, illustrates the proposed model. We demonstrate that the resulting evacuation strategies can be significantly different from conventional system optimal evacuation plans.

Tunneled Pleural Catheters for Treatment of Recurrent Malignant Pleural Effusion Following Failed Pleurodesis

To evaluate patient outcomes when tunneled pleural drainage catheters are placed for symptomatic, recurrent malignant pleural effusion following failed chemical pleurodesis. Two hundred seventy patients who underwent placement of a tunneled pleural catheter between January 2002 and December 2006 were retrospectively identified by reviewing interventional radiology billing records with institutional review board approval. Of these 270 patients, 63 (68 hemithoraces; 44 women, 19 men) with dyspnea were referred for tunneled pleural drainage catheter placement following failed pleurodesis for malignant pleural effusion. Clinical and procedural details were identified by chart review. Endpoints were technical success, symptomatic improvement in dyspnea, time to hospital discharge, and time to catheter removal or time to death with the catheter in place. Clinical improvement in dyspnea was noted in 60 of the 63 patients (95%). Fifty-seven of the 63 patients (90%) were discharged with their catheter in place after a median of 3 days (range, 0-29 days). Twenty-seven of the 63 patients (43%) were discharged in 2 days or less. Stays longer than 2 days were all associated with treatment of other medical problems. Twenty-one of the 68 catheters (31%) required fibrinolytic therapy for optimal evacuation of complex pleural collections. Eleven of the 68 catheters (16%) could subsequently be removed due to durable resolution of pleural effusion. The remaining patients died with catheters in place and no clinical evidence of catheter dysfunction after a median of 58 days. Even following failed pleurodesis, recurrent malignant pleural effusions can be effectively managed with placement of tunneled pleural catheters.

Analyzing evacuation decisions using multi-attribute utility theory (MAUT)

Emergency managers are faced with critical evacuation decisions. These decisions must balance conflicting objectives as well as high levels of uncertainty. Multi-Attribute Utility Theory (MAUT) provides a framework through which objective trade-offs can be analyzed to make optimal evacuation decisions. This paper is the result of data gathered during the European Commission Project, Evacuation Responsiveness by Government Organizations (ERGO) and outlines a preliminary decision model for the evacuation decision. The illustrative model identifies levels of risk at which point evacuation actions should be taken by emergency managers in a storm surge scenario with forecasts at 12 and 9 hour intervals. The results illustrate how differences in forecast precision affect the optimal evacuation decision. Additional uses for this decision model are also discussed along with improvements to the model through future ERGO data-gathering.

Analysis of near-optimal evacuation instructions

In this paper, approximations of optimal evacuation instructions are analyzed. The instructions, consisting of a departure time, a destination, and a route, are for the evacuation by car of a population of a region threatened by a hazard. An optimization method presented in earlier research is applied on three different hazard scenarios resulting in an instruction set for each scenario. These instruction sets are different because of network degeneration caused by the different hazard scenarios. Analysis of the network occupancy during the evacuations as consequence of the instruction sets shows that the capacity is used in the scenarios for minimal 87%, 90%, and 87% for the period wherein the effect of the network degeneration is relatively small. Although the results are logical, no clear patterns are perceptible in the instructions leading to this network occupancy. This endorses to the viewpoint from the earlier paper, namely, that it is useful to apply an optimization method to create evacuation instructions instead of applying instructions set up by straightforward rules (like evacuating to the nearest destination). Furthermore, it shows the efficiency of this specific optimization method.

Optimal Evacuation Plan Design with IP-Solver

This paper deals with two different computer-supported approaches to an evacuation plan design, which should assign the available vehicles to endangered dwelling places so that the total time of evacuation is minimal. It is assumed that some safe place is pre-assigned to each endangered dwelling place and there are determined locations of homogenous fleets of available vehicles, which can be used for transport of the endangered population from their dwelling places to the pre-assigned places. In this paper, we suggest and compare two approaches to the evacuation plan design. The first approach assigns all vehicles of a fleet to one evacuated dwelling place and the second one enables to assign individually any part of a fleet to the dwelling places.

Emergency evacuation planning as a network design problem: a critical review

Planning for emergency evacuation has evolved and matured substantially during the last two decades. The significant rise in natural and man-made disasters in recent years created a surge in the need for improved emergency evacuation planning. Voluminous studies, formulations, and control approaches have been presented in the literature with the common goal of improving the evacuation process to save precious time and lives. Proposed methods for improving the efficiency of emergency evacuation include reversing lanes in the direction of evacuation (contra-flow), staging the evacuation process, optimally controlling traffic, and providing route guidance to the evacuees. The objective of this paper is to review and compile the main strategies and approaches of emergency evacuation planning. Since most of these strategies can be generally viewed as a network design problem, particular attention has been given to briefly reviewing the network design problem (NDP) and the mutual mapping to the evacuation planning problem. In addition, this review touches upon the role of simulation in replicating the transportation network and the optimization in solving the evacuation problem. As we summarize the common schools of thought in evacuation planning, we critique the limitations, gaps, and challenges that hinder the development of an integrated optimal evacuation planning model. <i>We also propose a framework that compiles evacuation strategies, network design problem formulation, traffic simulation and optimization tools in an attempt to fill some of the identified gaps/limitations.</i>

A Generic Method to Optimize Instructions for the Control of Evacuations

A method is described to develop a set of optimal instructions to evacuate by car the population of a region threatened by a hazard. By giving these instructions to the evacuees, traffic conditions and therefore the evacuation efficiency can be optimized. The instructions, containing a departure time, a destination, and a route, are created using an optimization method based on ant colony optimization. Iteratively is searched for an approximation of the optimal evacuation instructions. The usefulness of the optimization method compared to other optimization methods is the simultaneous optimization of the departure time, destination, and route instructions instead of the optimization of only one or two of these variables for a dynamic instead of static evacuation problem. In a case study, the functioning of the method is illustrated. The relative high fitness in the case study of the set of instructions following from the optimization method compared with the fitness of a set of instructions set up by straightforward rules (like evacuating to the nearest destination) shows also the usefulness of applying an optimization method to create a set of evacuation instructions.

Inflation-deflation method for endoscopic evacuation of intracerebral haematoma

Endoscopic evacuation of intracerebral haematoma (ICH) has the advantage of being less invasive than craniotomy, but limited visualisation and difficulties in haemostasis are still a concern. The collapse of the haematoma cavity limits the visualisation of the surgical field. Inflation of the haematoma cavity with saline irrigation improves visualisation and facilitates accurate intra-operative orientation. A unique technique, the cavity inflation-deflation method can help in exploring the residual haematoma and accessing the bleeding points. We also developed a combined irrigation-coagulation suction tube that concentrates the capabilities of suction, irrigation and monopolar coagulation. The use of this multifunctional dedicated instrument and its application in the cavity inflation-deflation method allows for easy identification of residual haematoma and bleeding vessels. Secure haemostasis can also be accomplished under clear visualisation. No surgical complications and rebleeding occurred in any patient following the procedure. Our results show that the median haematoma evacuation rate was 99% and the surgical outcome was satisfactory. The inflation-deflation method using a combined irrigation-coagulation suction tube can facilitate optimal evacuation of ICH with secure haemostasis. Although further accumulation of patients and careful analyses are needed to be known whether this procedure improves the clinical outcomes in the patients, the preliminary results of its application have been promising.

Subglottic Secretion Viscosity and Evacuation Efficiency

Ventilator-associated pneumonia (VAP) is a common nosocomial pneumonia that occurs in critically ill patients and results in mortality rates as high as 71%. Subglottic secretions (SSs) are a known risk factor. Several clinical trials have shown that continuous aspiration of subglottic secretions (CASS) reduces the risk of VAP by nearly half. Optimal suction pressure levels needed to efficiently evacuate viscous SSs are unknown. The purpose of this study was to describe SSs and the effective suction pressure (20 mmHg, 30 mmHg, 40 mmHg, and 50 mmHg) needed to maximize evacuation efficiency based on SS volume (2 ml, 4 ml, and 6 ml) and viscosity (watery, thick, and gel-like). A laboratory model was designed to replicate a human trachea. Thick secretions had the highest percentage of mean recovery representative of evacuation efficiency of SSs (mean recovery of 86%). The suction pressure of 30 mmHg had the highest overall mean of secretion recovery (83%) across all viscosity types and amounts. This study demonstrated that higher viscosity secretions were easier to evacuate than lower viscosity secretions when 30-mmHg suction pressure was applied. Management of secretion viscosity may assist in secretion removal and delay VAP development. With increased understanding of the molecular structure of SSs, there is the potential that clinicians will be able to manipulate secretion viscoelastic properties to maximize evacuation efficiency of the secretions. Further research is needed to identify safe suction pressures for optimal evacuation of SSs in human subjects.

Two-Level Integrated Optimization System for Planning of Emergency Evacuation

This paper presents a two-level integrated optimization system for use in generating the candidate set of optimal evacuation plans that serve as the input for simulation-based evacuation systems. In the proposed system, the high-level optimization aims to maximize the throughput during the specified evacuation duration, and the low-level optimization is intended to minimize the total travel time as well as the waiting time for the entire operation if the specified duration is sufficient for meeting all evacuation demands. To effectively represent traffic flow relations with mathematical formulations, this paper employs the cell transmission concept, but with a revised formulation for large-scale network applications. The performance of the proposed models and their applicability has been tested with a microscopic simulation program that replicates the Ocean City evacuation network. Evaluation results from these numerical studies have demonstrated the promising properties of the proposed integrated optimization system.

THE ROLE OF PANIC IN THE ROOM EVACUATION PROCESS

In the present work we studied the room evacuation problem using the social force model introduced by Helbing and coworkers. The "faster is slower" effect induced by panic was analyzed. It could be explained in terms of increasing mean clogging delays which shows a strong correlation with certain structures that we call "blocking clusters". Also a steady state version of the problem was implemented. It shows that, from a macroscopic point of view, the optimal evacuation efficiency correspond to the state at which the difference between the system desire force minus the system granular force is maximum.

Endoscopic evacuation of putaminal hemorrhage: how to improve the efficiency of hematoma evacuation

Background A unique method of evacuation of hypertensive putaminal hemorrhage (HPH) using a stainless steel tube as a corridor under the assistance of a rigid endoscope is described. A simplified method to determine the precise location for burr hole placement is also reported. Methods From May 2003 to April 2004, 9 patients with HPH underwent endoscopic surgery in our hospital. Two different entry sites (temporal and frontal) were used to approach the hematoma in our series. Results The hematoma evacuation rate was more than 90% (median 93%) with the frontal approach and 84% with the temporal approach. Conclusions Using a combination of a stainless steel tube, rigid endoscope, and coagulation suction with a frontal approach can facilitate optimal evacuation of HPH.

A Risk Based Approach to the Development of Evacuation Plans in the Mine Subsidence Area Along the Meuse

The “Mijnverzakkingsgebied) (mine subsidence area) is located in the eastern part of Belgium along the River Meuse and is affected by subsidence up to seven meters due to historical mining activities. The subsidence is so large that during high flood stages in the river Meuse the area is under severe risk of flooding if one of the surrounding dikes would break. In such a case water depth in the area could locally reach 7 meters. This would lead to great damage to the houses and economic activities in the region. To minimize the victims and damage in the event of a dike failure, different evacuation plans were set up, which were based on two-dimensional inundation maps of the study area. These flooding scenarios were simulated assuming dike breaches at various locations. Applications of calibrated one-dimensional and two-dimensional hydraulic models of the river Meuse and the mine subsidence area enabled analyzing maximum water depth, the time-to-flooding and local water depth fluctuations during an inundation. Both applied hydraulic models were fed with recent and accurate bathymetry and topographical data from a detailed DEM monitored via laserscanning. The input data was of high quality which enabled one to carry out the analysis on a resolution of 25 meters. A combination of the different inundation maps and the local streetmaps gives an insight into the optimal evacuation direction for the inhabitants of the different villages. The different scenarios show also that certain regions can be flooded with inundation depths of more than 5 meters. In these regions, people have to be evacuated immediately by helicopter.

Cut-through switching, pipelining, and scheduling for network evacuation

A general model of a virtual circuit network consisting of a number of servers and a number of traffic classes is considered. A traffic class is identified by the sequence of servers that should be visited and the corresponding service rates before a message (customer) of the class leaves the network. The following cases are distinguished: (1) the messages need nonpreemptive service; (2) the service of a message can be preempted at any time; (3) pipelining of the service in a sequence of servers is allowed; and (4) pipelining is not allowed. All of these cases arise in different transmission switching techniques and scheduling schemes. A fluid model that emerges when both preemption and pipelining are allowed is considered. Scheduling schemes in the fluid model are compared with corresponding ones in the network with nonpreemptive service and no pipelining. The problem of evacuating the network from an initial backlog without further arrival is identified in the fluid model. Based on that, a policy with nearly optimal evacuation time is identified for the store-and-forward case. Finally, scheduling with deadlines is considered and it is shown that in the fluid model, the evacuation problem is equivalent to a linear programming problem. The evacuation times under different work-conserving policies are considered in specific examples.