A Fraternity Of Danger

A bstract . Interviews and participation with members of rural volunteer fire departments (VFDs) in New York State, indicate that local communities in rural regions are structured around VFDs. Such "communities" involves both the fraternity of the fire house, resting on the teamwork essential to firefighting, and a wider locality, which the VFDs spatially define and symbolically integrate through a ritual of parades, fund raising efforts, and their example of community service. The working class, attached to the locality by stable residence and recruited intergenerationally into the fire service, supplies the majority of volunteers.
Neoliberal modernization threatens this recruitment pattern. Problems have developed because the "new middle class" rejects VFD participation, except as ambulance volunteers. As localities compete for outside investment through the reduced cost of their services, they have exploited volunteers to provide fire protection at less cost than that of paid departments. This commodification of the VFDs risks destroying their character as a system of moral obligation unifying a locality and is an inequitable, and unsustainable, "tax" on working class volunteers. But innovative systems of emergency and other services can be used to attract the new male and female middle class into volunteer local activities.     

GIS-based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul,Turkey

Fire stations play a central role in protection and response activities as part of emergency management services in cases of fire incidences. With the rising urban populations and city expansions, the demand for more fire services resultantly increases. It then becomes critical to effectively plan the location of emergency facilities to adequately service the population and ensure the protection of lives and infrastructure. This study, therefore proposes the use of the fuzzy extension of the Multi-Criteria Decision-Making (MCDM) method of Analytical Hierarchical Process (AHP), hence called fuzzy AHP, integrated with Geographic Information Systems (GIS) approach to optimally site new fire stations for the case of Istanbul region. This proposed fuzzy approach simulates the subjective expert judgements for the preferences of the six criteria assessed for fire station suitability mapping and thereby accounted for the uncertainty of crisp comparison values via triangular fuzzy numbers (TFNs). The criteria weights evaluated from this procedure were used in a weighted overlay analysis of the reclassified criteria map layers in ArcGIS to generate a fire station suitability map. These resultant fuzzy AHP criteria weights were validated using another MCDM technique, called Best-Worst Method (BWM) and found to be comparable and consistent. The criteria that had the strongest influence on the selection of sites for fire stations were identified to be: the density of hazardous material facilities (DHM), a high population density (HPD) and proximity to main roads (PMR) with associated weights of 33.3%, 24.4% and 15.2%, respectively. Based on a thorough assessment within the areas represented by class values ranging from 3 to 5 on the suitability map, a total of 34 new fire station sites were selected complementing the existing 121 fire stations. Further, a prioritization analysis from low, medium to high, was performed to plan the phases for the construction of new fire stations in view of competing budgetary needs and resource constraints. The methodology to achieve this was proposed and modelled for enhancing the decision-making process in urban fire station site selection studies.     

Ambulance response time in a Brazilian emergency medical service

Research efforts on ambulance response times for Emergency Medical Services (EMS) calls have been made for decades, especially in developed countries, using different techniques and with varying objectives. In Brazil, a developing country, the scarce scientific production on this vital indicator prioritizes scenarios for EMS in cities with more than one million inhabitants. This shows the importance of extending research to the reality of small and medium-sized cities. This paper presents SAMU, the Brazilian EMS that follows the Franco-German emergency medicine model, compiling numbers related to service at the national level. The use of quantile regression allows the identification of the RT for the EMS and helps to explain the effects of factors at the system level, at the patient level, and specific factors on response time intervals of Southwest Paraná SAMU. This specific EMS, characterized as an inter-municipal consortium of prehospital services, is responsible for prehospital emergency care for an approximate population of 635,000 inhabitants in 42 small towns in the State of Paraná in southern Brazil. From the analysis of the records of 12,050 ambulance dispatches, it was possible to identify the average ambulance response time of 14 min and 25 s. The regression model was able to explain the influence of the independent variables at the system level (presumed severity of the emergency, ambulance dispatch time, and ambulance travel time), at the patient level (age, gender, and characteristic of the emergency) and specific variables of the emergency (day of the week and time of day) on the dependent variable response time over the quantiles, showing that the dispatch time, travel time, time of day, service to male patients and critical cases influence the ambulance response time. This work contributes to deepening the understanding of the management of EMS operations in a developing country, allows the comparison of the RT identified in relation to other countries, and identifies factors that impact the RT for other actors directly or indirectly involved. The practical implications are also presented, as well as how the study impacts the decision-making and management process of the EMS in the short, medium and long term.     

Incorporating activity space and trip chaining into facility siting for accessibility maximization

Location models have been widely used to support locational decisions for various service provision. One common objective of location models has been to ensure maximal accessibility of sited facilities to demand populations. Accessibility evaluation in location models often assumes that trips originate from fixed locations (usually home) and are single purpose. These assumptions contradict the empirical evidence that suggests trips also commonly originate from non-home locations and may involve multiple stops. In this study, a new multi-objective location model is developed that extents the classic p-median problem (PMP) to account for a more realistic assessment of accessibility. Based on the individual accessibility assessment, notions of trip chaining and activity space are incorporated into the model development. In addition to fixed home locations, stops along chained trips are allowed for potential service site visits, and activity space is introduced as an additional dimension to evaluate accessibility of alternative opportunities. The effectiveness of the new model is demonstrated using an application in Tucson, AZ.     

A Hybrid model for locating new emergency facilities to improve the coverage of the road crashes

We propose an emergency facility-locating model aimed at increasing the coverage of emergency demand throughout the city. The proposed model takes into account the status and location of the emergency facilities in the network and identifies locations suitable for the construction of new facilities. Here, Data Envelopment Analysis (DEA) and Maximum Coverage Location Problem (MCLP) have been combined in a single model. To do so, design problem and evaluation problem are considered concurrently to maximize the efficiency of services provided by emergency facilities across the city in response to the demand. Moreover, the total emergency demand in each district was considered in relation to the population density, the fatal, injurious, and property damage only (PDO) crashes. The coverage area of each emergency facility was assumed to be proportional to the average ambulance speed in the surrounding road network during rush hours. The available budget was included in the model to let the model function under various fiscal conditions. Model input variables consisted of average number of mortalities, injuries and PDO crashes as well as the population density of each urban district. The output variables of the model included the coverage share of proposed emergency centers and hospitals equipped with ambulances. The model was tested on the network of Tehran (Iran). It is recommended to add the location of some emergency centers and hospitals to the network. Moreover, the results showed that ten urban districts had efficiency problem in provision of emergency services.     

Minimising emergency response time of ambulances through pre-positioning in Dhaka city,Bangladesh

This study conducted a large-scale survey in Dhaka, Bangladesh; the survey involved 95 major hospitals, more than 3000 emergency room patients, and 2 of the largest ambulance operators. Currently, most ambulances are parked within the vicinity of hospitals and are either dispatched or fetched by the acquaintances of the patient on demand, resulting in lengthy round trips. Reducing the response time of ambulances would certainly improve the emergency service, and pre-positioning of the ambulances could be a solution to reducing the response time. This study used two approaches to address the problem. First, the location-allocation problem was solved to find the optimal number of ambulance locations by maximising the demand coverage. Second, separate location-allocation for the peak and off-peaks, using K-means clustering, was applied to systematically optimise the ambulance positioning in small clusters near demand points. These approaches could substantially improve the existing emergency response time. Distributing ambulances near demand points yielded greater improvements in response time than when the ambulances are stationed near hospitals.     

Reorganizing an existing volunteer fire station network in Germany

Volunteer fire departments have been founded to ensure public safety in case of fire and to provide support for professional firefighters. Most of the current stations date back to the beginning of the 19th century. Today, volunteer fire departments face numerous challenges, such as reduced number of following young volunteers or decreasing public budgets. We quantify these effects and identify different alternatives, such as relocating or closing of stations to minimize the impact on rescue service supply. Based on comprehensive case studies in Bochum, Germany it is apparent that these recommendations provide an excellent toolset for a prospective planning approach.     

Locating fire stations: An integrated approach for Belgium

This paper illustrates the potential of a decision-support system developed for Belgium by a consortium of universities and a private firm, in the framework of a public call made by the Ministry of the Interior. The system is designed to provide the Belgian emergency management administration with a complete decision-aid tool for the location of fire stations. The originality of the project is that it includes a risk-modeling approach developed at a national scale. This analysis involves a multiscale GIS that includes a thorough representation of the physical, human and economic spatial realities, a risk-modeling approach, an adequate optimal location and allocation model (taking into account both queuing and staffing problems). The final result is an interactive operational tool for defining locations, equipment allocations, staffing, response times, the cost/efficiency trade-off, etc. This flexible tool can be used in an assessment as well as a prospective context. It has been used to draw a national reorganization plan for fire stations that started being implemented in 2010.     

Simulation modeling and optimization for ambulance allocation considering spatiotemporal stochastic demand

To ensure a timely response to emergencies, governments are obliged to implement effective ambulance allocation plans. In practice, an emergency medical service (EMS) system works in an uncertain environment, with stochastic demand, response-times, and travel-times. This uncertainty significantly affects ambulance allocation planning. However, few studies in this field adequately consider the effect of spatiotemporal uncertainty in demand, because it is difficult to measure it quantitatively. As a result, few analytic models capture the dynamic nature of an EMS system and, thus, the allocation plans they generate are not efficient in practice. Therefore, this study proposes a simulation-based optimization method for ambulance allocation. A simulation model is constructed to mimic the operational processes of an EMS system, and to evaluate the performance of an ambulance allocation plan in an uncertain environment. Gaussian mixture model clustering is used to derive the uncertain spatial demand. Then, the simulation generates emergency demand based on the obtained spatial distribution. A Gaussian-process-based search algorithm is used together with the simulation model to identify optimal solutions. To validate the proposed method, a case study is conducted using data on emergency patients in the Shanghai Songjiang District. Compared with the current plan adopted in Songjiang, the experimental results demonstrate that the delay time and frequency of the EMS system can be reduced significantly by employing the proposed methods. Furthermore, nearly 41% of the allocation cost can be saved.     

Application of an Analytic Hierarchy Process (AHP) in the GIS interface for suitable fire site selection: A case study from Kathmandu Metropolitan City,Nepal

Kathmandu Metropolitan City, the capital city of Nepal, is prone to different types of disasters. Fire disaster is one of the most recurring in the city. Due to haphazard urbanization, poor fire services, few and old fire engines, insufficient skilled human resources combined with narrow road lanes, clustered households increase the fire vulnerability in Kathmandu Metropolitan City. This paper documents the fire station suitability zonation mapping in Kathmandu Metropolitan City using Group Decision Making Process (GDMP) in the GIS interface. Four different selection criteria factors such as distance from roads, land cover, distance from rivers and population density are considered for analysis and the Analytic Hierarchy Process (AHP) is used for Group Decision Making Process (GDMP). The results reveal that only 13.46% of the study area is highly suitable for fire station location. Hence, the fire station suitability zonation map is trustworthy and can be used for the construction of new fire stations in Kathmandu Metropolitan City.     

A minimum expected response model: Formulation, heuristic solution, and application

Responding to true emergencies in the shortest possible time saves lives, prevents permanent injuries and reduces suffering. Most covering models consider an emergency cover if an ambulance is available within a given time or distance threshold. From a modeling perspective, shorter or longer responses within this threshold are all tallied as covered; conversely, the emergencies immediately outside the threshold are considered uncovered. However, if the shorter responses are given more weight along with the volume of such incidents, while still meeting system-wide coverage requirements, both customers and providers can benefit from reduced response times. We formulate a model to determine the locations for a given set of ambulances to minimize the system-wide expected response distances while meeting coverage requirements. We solve the model with a heuristic search algorithm and present computational and comparative statistics using data from an existing Emergency Medical Services agency.     

Feasibility on the integration of passenger and freight transportation in rural areas: A service mode and an optimization model

Public transport operators in rural areas have been under pressure from weak profitability and emission issues. At the same time, scattered demand for transport has been preventing logistics systems from reaching the last mile in residential areas. Multimodal transport can synergistically integrate passenger and freight demand, increase transportation network coverage, and reduce the cost of transportation, while demand-driven services improve the flexibility and reliability of operational decisions. Therefore, this paper proposes a demand-driven passenger-and-freight-integration service (DDPFIS) mode. From the perspective of routing decisions, a new mixed-integer linear programming model based on the green vehicle routing problem is formulated to assist public transport operator’s complex decision-making. In the proposed model, vehicle capacity is fully utilized through a combination of passenger and freight demand so that optimal decisions are made about vehicle routing. Numerical experiments are designed and conducted based on realistic instances with the results indicating that: the DDPFIS mode enables effective integration of different demands, leading to high-level vehicle capacity utilization and cost reduction; and compared with two conventional models of vehicle routing problems, the proposed model achieves lower fuel consumption and cost for all problem sizes. In addition, some important management insights are provided, e.g., a greater proportion of integrated service nodes is not necessarily better; and it is more suitable to provide a service for rural residents who are relatively insensitive to time.     

模糊层次分析法在地铁站火灾风险评估中的应用

随着城市公共交通的快速发展,地铁已成为人们出行的一种重要交通工具,但地铁站火灾近年来时有发生,对地铁站运行过程中的火灾风险进行合理评估是保证地铁安全运行的前提。论文基于模糊层次分析法构建了地铁站运行过程中火灾风险评估模型,并将该模型进行了实际运用。     

Siting a facility in continuous space to maximize coverage of a region

Siting facilities in continuous space such that continuously distributed demand within a region is optimally served is a challenging location problem. This problem is further complicated by the non-convexity of regions typically encountered in practice. In this paper a model for maximizing the service coverage of continuously distributed demand through the location of a single service facility in continuous space is proposed. To address this problem, theoretical conditions are established and associated methods are proposed for optimally siting a service facility in a region (convex or non-convex) with uniformly distributed demand. Through the use of geographic information systems (GIS), the developed approach is applied to identify facility sites that maximize regional coverage provided limitations on facility service ability.     

高校快递纸箱回收再利用网络节点选址研究--以郑州大学为例

为解决高校快递纸箱回收再利用问题,提出构建高校快递纸箱回收再利用层级网络,并确定层级网络中物流节点的选址布局。首先,基于现有校园快递服务点,构建包括消费点、回收站、处理中心和快递服务点的四级快递纸箱回收再利用层级网络。然后,以成本最小化为目标构建高校快递纸箱回收再利用网络节点选址模型。最后,以郑州大学为例,确定了郑州大学新校区快递纸箱回收再利用网络中回收站和处理中心的选址,验证了模型的可行性。     

Critical infrastructure location under supporting station dependencies considerations

This paper develops a framework to locate critical infrastructure (CI) facilities to most fully capitalize on the supporting stations (SSs) they depend on for normal operation. CI facilities include health services, transportation and electricity; agencies that impact the national economy, security and the public's health and wellbeing. SSs are facilities that provide essential services for the regular operation of a CI. For instance, the power service, communication services and water supply services are SSs for Hospitals. In this paper SSs are independent from the CIs that they service and have a heterogeneous probability of failure that will cripple the dependent CI. The proposed framework ranks the SS according to its cost of providing service such that the rank-1 SS is the primary service provider and incorporates the probability of failure for the SS. The CI will be served from secondary SS if the primary fails due to a disaster. This formulation insures the continuous service to the CI from SS and determines both the optimal location of the CI and the optimal number of demands served. A mixed integer linear programming approach is applied to develop a Reliable Facility Location Problem considering Supporting Stations (RFLP-SS) to identify the optimal location to build a critical facility. In addition to that, The RFLP-SS determines the capacity of the optimally located facility and its allocated demands. This research highlights the importance of considering dependencies among the SSs that service CI. The paper presents a case study in Puerto Rico to demonstrate the applicability of the proposed framework. The case study investigates the status of health services in Puerto Rico, and identifies the optimal locations to establish new hospitals. The paper recommends 11 locations for new hospitals so that the people of Puerto Rico will be better served than they are currently.     

Network planning of fuelling service stations in a near-term competitive scenario of the hydrogen economy

Hydrogen can be viewed as the flexible automotive fuel of the future. However, many issues related to its use have not been sufficiently investigated. One such issue concerns hydrogen logistics and distribution throughout a territory. One near-term scenario over the next decade is likely to include distribution procedures that are similar to those currently used for petrol products. In this scenario, the conversion of petrol service stations into hydrogen distribution points will progressively be implemented. Petrol companies will then represent one of the major categories of hydrogen producers. They will thus have to select, from a cost/benefit standpoint that accounts for competing companies expected to offer the same service throughout a territory, the most convenient and effective locations for hydrogen distribution. The current paper presents a model for planning a network of service stations of a given company within a competitive framework. A case study of a specific territory in northern Italy is presented and discussed.     

集成GIS的供应链结构模型探析

当今，信息技术日新月异，如何利用它们重组和优化供应链，降低动作成本，提高客户的服务水平和整条供应链的竞争能力将是一个刻不容缓的问题，把GIS技术应用于供应链管理之中日益受到关注和重视。本文首先介绍了地理信息系统（GIS）的相关知识和供应链的通用结构模型：据此构建了集成GIS的供应链结构模型：并从表现形式、查询检索、决策分析、高度集成等几方面分析了新模型的特征，对GIS在供应链管理中的具体应用具有一定的指导和借鉴意义。     

Mathematical analysis of emergency ambulance location

Proper ambulance location is crucial in saving lives and reducing injury. To determine efficient and effective locations, it is necessary to evaluate both the spatial and temporal distributions of demand. Because of the complex nature of the ambulance response and transport activities, the problem is subdivided into a facility location problem and a vehicle allocation problem. A set covering model is modified to solve the location problem while a simulation is used to solve the allocation problem. Combining these two models provides a powerful methodology for systematically finding a satisfactory solution to the ambulance location problem.     

Improving social harm indices with a modulated Hawkes process

Communities are affected adversely by a range of social harm events, such as crime, traffic crashes, medical emergencies, and drug use. The police, fire, health and social service departments are tasked with mitigating such social harm through various types of interventions. While various different social harm indices have been proposed for allocating resources to spatially fixed hotspots, the risk of social harm events is dynamic, and new algorithms and software systems that are capable of quickly identifying risks and triggering appropriate public safety responses are needed. We propose a novel modulated Hawkes process for this purpose that offers flexible approaches to both (i) the incorporation of spatial covariates and leading indicators for variance reduction in the case of rarer event categories, and (ii) the capture of dynamic hotspot formation through self-excitation. We present an efficient l1-penalized EM algorithm for estimating the model that performs feature selection for the spatial covariates of each incident type simultaneously. We provide simulation results using data from the Indianapolis Metropolitan Police Department in order to illustrate the advantages of the modulated Hawkes process model of social harm over various recently introduced social harm indices and property crime Hawkes processes.