Emergency Resource Allocation Research Articles

An Integrated Optimization of Emergency Resource Allocation and Route Planning Using Workflow Net

An Integrated Optimization of Emergency Resource Allocation and Route Planning Using Workflow Net

A first approach to a hybrid algorithm for mobile emergency resources allocation

We present a hybrid algorithm based on Genetic Algorithms and Discrete Event Simulation that computes the algorithmic-optimal location of emergency resources. Parameters for the algorithm were obtained from computed historical statistics of the Bogotá Emergency Medical Services. Considerations taken into account are: (1) no more than a single resource is sent to an incident, (2) resources are selected according to incidentpriorities (3) distance from resource base to incident location is also considered for resource assignment and (4) all resources must be used equally. For every simulation, a different set of random incidents is generated so it’s possible to use the algorithm with an updated set of historical incidents. We found that the genetic algorithm converges so we can consider its solution as an optimal. With the algorithmic-optimal solution we found that arrival times are shorter than the historical ones. It’s also possible to compute the amount of required resources to reduce even more the arrival times. Since every Discrete Event Simulation takes a considerable amount of time the whole algorithm takes a heavy amount of time for large simulation time-periods and for many individuals for generation in the genetic algorithm, so an optimization approach is the next step in our research. Also, less restricted considerations must be taken into account for future developments in this topic.

Research on the risk-based model for regional emergency resource allocation for ship-source oil spill

The key point for rational allocation of emergency resources is to match the oil spill response capacity with the risk of oil spill. This paper proposes an innovative risk-based model for quantitative regional emergency resource allocation, which comprehensively analyzes the factors such as oil spill probability, hazard consequences, oil properties, weathering process and operation efficiency, etc. The model calculates three major resources, i.e., mechanical recovery, dispersion and absorption, according to the results of risk assessment. In a field application in Xiaohu Port, Guangzhou, China, and the model achieved scientific and rational allocation of emergency resources by matching the assessed risk with the regional capacity, and allocating emergency resources according to capability target. The model is considered to be beneficial to enhancing the resource efficiency and may contribute to the planning of capacity-building programs in high-risk areas.

A Multiobjective Allocation Model for Emergency Resources That Balance Efficiency and Fairness

Efficiency and fairness are two important goals of disaster rescue. However, the existing models usually unilaterally consider the efficiency or fairness of resource allocation. Based on this, a multiobjective emergency resource allocation model that can balance efficiency and fairness is proposed. The object of the proposed model is to minimize the total allocating costs of resources and the total losses caused by insufficient resources. Then the particle swarm optimization is applied to solve the model. Finally, a computational example is conducted based on the emergency relief resource allocation after Ya’an earthquake in China to verify the applicability of the proposed model.

Planning emergency in historical centres: from vulnerability to the definition of urban risk maps

Historical centres are high-risk scenarios for evacuees during earthquake emergency. Herein, the preventive identification of criticalities concerning the emergency paths is important to preserve evacuees’ and rescuers’ safety and design effective risk mitigation solutions. This study proposes new indices for the quick evaluation of paths’ vulnerability and of possible debris amounts blocking the evacuation paths within the historical centre. Furthermore, starting from the obtained indices, the study produces probabilistic risk maps of the centre useful before and after emergency to plan the safe paths for evacuees and rescuers, design emergency operations and resource allocation.

Site Selection and Resource Allocation of Oil Spill Emergency Base for Offshore Oil Facilities

Based on the analysis of the historical data about oil spill accidents in the Bohai Sea, this paper discretizes oil spilled source into a limited number of spill points. According to the probability of oil spill risk, the demand for salvage forces at each oil spill point is evaluated. Aiming at the specific location of the rescue base around the Bohai Sea, a cost-benefit analysis is conducted to determine the total cost of disasters for each rescue base. Based on the relationship between the oil spill point and the rescue site, a multi-objective optimization location model for the oil spill rescue base in the Bohai Sea region is established. And the genetic algorithm is used to solve the optimization problem, and determine the emergency rescue base optimization program and emergency resources allocation ratio.

Optimized maritime emergency resource allocation under dynamic demand.

Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

The Second Opinion Dispatch- Evaluating Decisions Made by an Ambulance Dispatch Center

BACKGROUND: The efficacy and precision of dispatching right ambulance to right patient demands a proper decision-making. Wrong decisions may lead to overloading of emergency departments and shortage of ambulances. The aim of this study was to evaluate and improve the process of prehospital resource allocation conducted by a Swedish ambulance dispatch center.METHODS: A team of three experienced ambulance and dispatch nurses evaluated the decisions made by the dispatch center. The method chosen was “Action Research” divided into five actions during 76 days. In the first action, the team listened passively to the calls. The team gradually increased its involvement in the process of decision-making during the actions.RESULTS: During the actions, specific keywords indicating a need for evaluation were identified. The results showed a need to change the primary decisions in 486 cases out of 24,800 calls (2%). The most common measure after an evaluation was to change an ordinary ambulance transportation to an assessment vehicle staffed by a nurse or a physician who would select an appropriate care level (hospital vs. primary healthcare).CONCLUSION: This model not only optimized the prehospital resources but also changed the process of decision-making at the dispatch center and improved their staffs’ ability to optimize the allocation of emergency resources.

Optimized traffic emergency resource scheduling using time varying rescue route travel time

Abstract Traffic emergency resource scheduling not only needs to satisfy the type and quantity of resources required for traffic incidents, but also to consider the change of traffic state before making the rescue decision. For this purpose, a traffic emergency resource scheduling method based on rescue route travel time estimation was proposed. Considering the vehicle queuing phenomenon in the rescue route caused by traffic incidents, the rescue route travel time was defined as the sum of free flow travel time and queuing delay time. The queuing section was shifted to the downstream of the section and making the free flow section and queue section regarded as two continuous sections. Then according to the relative relationship between the total length of rescue route and the queuing delay time of rescue vehicles, the rescue route travel time was estimated and the improved resource scheduling model was established. As shown by the emergency resource scheduling application in the expressway network of Henan province, the simulation results of rescue route travel time estimation and the scheduling model revealed that the queuing delay time directly affects the computation of the rescue travel time. In addition, using branch and bound algorithm to obtain the optimized emergency resource scheduling scheme, the proposed scheduling model could enhance the effectiveness and efficiency of emergency resource allocation and improve the road traffic safety.

Multistage assignment optimization for emergency rescue teams in the disaster chain

Human resources and potential secondary disasters are often neglected in the existing emergency resource allocation methods. This paper presents a multistage assignment model for rescue teams to dynamically respond to the disaster chain and develops three priority scheduling strategies defined under the burden-benefit accord principle. A designed NSGA-II, C-METRIC and fuzzy logic methods were developed to solve the above multi-objective integer nonlinear programming model. Finally, the experimental scenarios results indicated that the overall performance of the proposed method was satisfactory in comparison with current method regardless of whether the secondary disasters occurred sooner or later. It was demonstrated that the three proposed priority scheduling strategies outperformed the others; however, which of these three priority strategies is most appropriate for a specific disaster situation depends on the maximum rescue time allowed by the disaster.

The relationship between emergency department volume and patient complexity

IntroductionForecasting emergency department (ED) visits is a well-studied topic. The importance of understanding the complexity of patients along with the days and times of varying patient volumes is critical for planning medical and ancillary staffing. Though multiple studies stratify their results based on severity of disease, severity was determined by triage status. The goal of this study was to utilize a novel method to evaluate the correlation between daily emergency department patient complexity, based on Current Procedure Terminology (CPT) code, and day of the week. MethodsThis was a retrospective study of subjects presenting to the ED between January 1, 2010 and December 31, 2015. We identified the correlation between subjects with each CPT code who were evaluated on a specific day of the week and evaluated the day before, the day of and the day after a legal holiday. ResultsDuring the study period 312,550 (48%) male and 336,348 (52%) female subjects were identified. No correlation between daily ED patient complexity, based on CPT code, and day of the week (p=0.75) or any legal holidays were identified. Individual significant differences were noted among day of the week and particular CPT code as well as legal holiday and particular CPT code with no appreciable trend or pattern. ConclusionsThere was no correlation between daily ED patient complexity based on CPT code and day of the week or daily ED patient acuity and legal holiday. In light of these data, emergency department staffing and resource allocation patterns may need to be revisited.

Multi objective optimization of railway emergency rescue resource allocation and decision

Based on the characteristics and requirements of railway emergency resources dispatch, the paper established two optimal models respectively, the single objective model is aiming at minimizing the time of emergency resource dispatch, the multi objective model is for the sake of minimizing the time of emergency resource dispatch and the number of emergency rescue base, and the paper used voting analytic hierarchy process of operations research to solve the model. The study shows that the multi objective optimization model can reduce the number of emergency rescue base and the cost of rescue while it can meet the demand of the shortest allocation time. By using Matlab software, the decision-making process of emergency resource optimize dispatch was designed, making the emergency decision fast and scientific, meanwhile, the paper made an empirical analysis on one railway bureau. The research results reduce the rescue time and cost of the railway accident, and provide reference for implement the rapidness response to make decision on emergency resources allocation, scientific resource allocation decisions.

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence.This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities.The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities.

A Feeder-Bus Dispatch Planning Model for Emergency Evacuation in Urban Rail Transit Corridors.

The mobility of modern metropolises strongly relies on urban rail transit (URT) systems, and such a heavy dependence causes that even minor service interruptions would make the URT systems unsustainable. This study aims at optimally dispatching the ground feeder-bus to coordinate with the urban rails’ operation for eliminating the effect of unexpected service interruptions in URT corridors. A feeder-bus dispatch planning model was proposed for the collaborative optimization of URT and feeder-bus cooperation under emergency situations and minimizing the total evacuation cost of the feeder-buses. To solve the model, a concept of dummy feeder-bus system is proposed to transform the non-linear model into traditional linear programming (ILP) model, i.e., traditional transportation problem. The case study of Line #2 of Nanjing URT in China was adopted to illustrate the model application and sensitivity analyses of the key variables. The modeling results show that as the evacuation time window increases, the total evacuation cost as well as the number of dispatched feeder-buses decrease, and the dispatched feeder-buses need operate for more times along the feeder-bus line. The number of dispatched feeder-buses does not show an obvious change with the increase of parking spot capacity and time window, indicating that simply increasing the parking spot capacity would cause huge waste for the emergent bus utilization. When the unbalanced evacuation demand exists between stations, the more feeder-buses are needed. The method of this study will contribute to improving transportation emergency management and resource allocation for URT systems.

Analysis of pre-hospital emergency resources allocation in Liaoning province

Objective To learn the present pre-hospital emergency resources allocation in Liaoning province. Methods Site survey and questionnaire survey were used to survey the basic information, number of pre-hospital emergency ambulances, human resources, and communication/control systems of 19 pre-hospital emergency centers in Liaoning province in 2014. Results The number of pre-hospital emergency sub-stations, ambulances and human resource fall short of demand.Furthermore, these resources are found with such problems as greater service radius of average pre-hospital emergency service and longer average pre-hospital response time in countryside than cities, insufficient and obsolete ambulances short of onboard equipment and communication systems, not to mention shortage of medical workers of higher degrees and academic titles. Conclusions A great gap is found between urban and rural pre-hospital emergency resource allocation in Liaoning province, with poor resources in the countryside.The government is recommended to step up financial support in increasing pre-hospital emergency substations and resources allocation, regularly update pre-hospital emergency vehicles, set up independent title promotion mechanism, perfect communication scheduling system, in order to satisfy the demands of pre-hospital first aid. Key words: Liaoning province; Pre-hospital emergency; Resources allocation; Aid effectiveness

A bi-objective robust model for emergency resource allocation under uncertainty

Emergency resource allocation constitutes one of the most critical elements of response operations in the field of emergency management. This paper addresses an emergency resource allocation problem which involves multiple competing affected areas and one relief resource centre under supply shortage and uncertainty in the post-disaster phase. In humanitarian situations, both the efficiency and fairness of an allocation policy have a considerable influence on the effectiveness of emergency response operations. Thus, we formulate a bi-objective robust emergency resource allocation (BRERA) model which tries to maximise efficiency as well as fairness under different sources of uncertainties. To obtain decision-makers’ most preferred allocation policy, we propose a novel emergency resource allocation decision method which consists of three steps: (1) develop a bi-objective heuristic particle swarm optimisation algorithm to search the Pareto frontier of the BRERA model; (2) select a coefficient to measure fairness; and (3) establish a decision method based on decision-makers’ preference restricted by the fairness coefficient. Finally, a real case study taken from the 5 December 2008 Wenchuan Earthquake demonstrates the effectiveness of the proposed method through numerical results. The solution and model robustness are also analysed.

Multiple emergency resource allocation for concurrent incidents in natural disasters

Emergency resource allocation, which mainly deals with how to efficiently allocate emergency resources of rescue agencies to process emerging incidents and reduce casualties and economic losses, has been one of the most fundamental and essential problems in emergency management for natural disasters. However, to our best knowledge, the existing deterministic methods concentrate on emergency resource allocation only for a single incident with constraints on response time or emergency resource cost separately, which is too simple to be applied in complex emergency scenarios. To this end, in this paper we commit ourselves to a challenging problem of allocating multiple emergency resources to multiple concurrent incidents in a parallel manner, taking response time and emergency resource cost altogether. For this purpose, we first define disaster response coalition as a form of team play. Besides, we propose a multiply constrained integer linear programming model and develop a differential evolution and heuristic based search algorithm to explore overlapping disaster response coalitions for concurrent incidents. Finally, the comparative experimental results show that technically, the parallel allocation of emergency resources for concurrent incidents is significantly more economical and efficient than the traditional serial allocation.

Review and Prospect of Studies on Emergency Management

In China, the occurrence of a series of disasters and the tremendous loss in human lives expose the vulnerability the emergency system and the incomplete of the methodology. Faced with the needs of the practice, this paper conducted a comprehensive review both from the system and the methodology prospective. From the system prospective, this paper aims at analyzing the existing problems and the solution finding. From the methodology prospective, emergency facility location problem, emergency resource allocation problem, and emergency management technical support problem are examined.

Modeling multiple humanitarian objectives in emergency response to large-scale disasters

In this paper, we characterize the humanitarian objectives of emergency resource allocation and distribution in disaster response operations. We formulate the humanitarian principles as three objective functions, i.e., lifesaving utility, delay cost and fairness. An integrated multi-objective optimization model that combines resource allocation with emergency distribution is developed, where a time space network is used to incorporate the frequent information and decision updates in a rolling horizon approach. The proposed model is shown to be a convex quadratic network flow problem, for which we design an efficient Variational Inequality algorithm. Computational results are reported to illustrate the performance of the proposed model and algorithm.

Location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling

Article history: Received January 29, 2015 Received in revised format: April 28, 2015 Accepted May 5, 2015 Available online May 7 2015 Distribution and optimum allocation of emergency resources are the most important tasks, which need to be accomplished during crisis. When a natural disaster such as earthquake, flood, etc. takes place, it is necessary to deliver rescue efforts as quickly as possible. Therefore, it is important to find optimum location and distribution of emergency relief resources. When a natural disaster occurs, it is not possible to reach some damaged areas. In this paper, location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling is investigated. In this study, there is no need to visit all the places and some demand points receive their needs from the nearest possible location. The proposed study is implemented for some randomly generated numbers in different sizes. The preliminary results indicate that the proposed method was capable of reaching desirable solutions in reasonable amount of time. Growing Science Ltd. All rights reserved. 5 © 201