Optimizing Fire Station Locations for the Istanbul Metropolitan Municipality (original) (raw)
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A GIS approach to fire station location selection
GI4DM 2011 GeoInformation For Disaster Management Conference
Location science has a long historical background and the literature of location selection has expanded since it attracts much interest from researchers. As a result of many studies the location science can be classified into several sub-categories; one of which is locating emergency facilities. The determination of locating fire stations is a crucial decision for metropolitans. Reducing response time, maximizing coverage and minimizing the total cost are the most important objectives for selecting the proper location. Using Geographic Information Systems (GIS) is important since it gives an opportunity to study on maps and to have coverage matrices which show the service areas in terms of binary integers and an attractiveness matrix which shows total values of closeness to main roads, residential areas, important buildings and so on. Fire stations have to be located carefully; in an emergency situation the fire department should be able to reach its destination within 5 minutes. Hence, the coverage matrix is very important for defining the potential of alternative locations. Mathematical model is based on the coverage and attractiveness matrices with the objectives of reducing response time, maximizing coverage and the minimizing the total cost. Taking the increasing population and traffic jam and the location in the earthquake zone into consideration, the fire stations have to be found at the most appropriate location in Istanbul to facilitate the arrival at the scene as fast as possible. This paper presents a decision support system approach for locating the fire stations via the geodatabase of Kadikoy district in GIS. In this study, GIS analysis and multi-objective mathematical model were used to consider the opportunities and the threats with strong and weak sides of the possible locations.
2019
The process of fire stations site selection is always traditionally based on the experience of a few people in some special organizations or with regard to available facilities in cities. On the other hand, the proper distribution of fire stations is essential in order to provide relief to vulnerable areas in times of crisis. In the meantime, the correct, accurate and scientific site selection of the fire stations will be an important step in improving the relief operation during the crisis. In this research, a hybrid model has been developed based on Network Analysis and Set Covering Location Problem (SCLP) for the site selection of fire stations in Tehran, Iran. At first, the areas that are covered by the 3-minute standard time of 112 existing fire stations were found on Tehran road network. Then the operational areas of the fire stations were divided into 308 sub-areas and the centers of these areas were considered as demand points in order to respond within the 3-minute standard...
The fire station location problem: a literature survey
Urban fire causes significant threat to the loss of lives and property. The location of a fire station is critical to reduce response time to incident place and eventually increase possibility of beating life-threatening dangerous flashovers. Fuzzy international standards, population density, traffic conditions and distance to other existing fire stations, fire resources and hazardous are some of the criteria considered in the fire station location problem. In this paper, we conduct a thorough literature survey of well-founded research that bring forth methodologies for better fire stations locations. It compares methodologies that adopt fuzzy multi-objective optimisation, maximal coverage, geographic information system (GIS), genetic algorithm (GA), ant algorithm, Tabu search (TS) and simulated annealing (SA) to solve the complex problem with higher efficiency and in due course of increasing possibility of rescue and survival. Reference to this paper should be made as follows: Aleisa E. (xxxx) 'The fire station location problem: a literature survey', Int.
Determination of Fire Station Coverage Area Using Response Time Approach: A Case Study of Samsun
2015
SUMMARY Fire and rescue stations play a key role in fire management. An early and aggressive primary attack will save more properties and lives in fire and rescue cases. A critical component in the control and mitigation of a fire incident is response time which includes travel time. Travel time is one of the most important elements of the response time and it is affected by various factors; such as traffic volume, road networks, time of day, driver habits, and the location of the incident. The strategic locations of fire stations are of paramount importance in achieving a minimal travel time. In this study, existing sites of fire stations in Samsun city were evaluated according to the location of emergency calls and the 5, 10, 15 minutes response time coverage area using the Geographic Information System (GIS) network analysis
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN
This research aims to apply the spatial analysis to optimize the placement of firefighting units in the area of South Jakarta. The calculation and pre-analysis shown that there are some uncovered service areas at South Jakarta. Therefore, the recalculation and analysis help to find out the strategic new possible location for the fire station. Optimalization of the location of the new fire station is conducted by calculating the minimum time travel from help point to fire point. Other than that, the minimum time travel also calculated based on actual blocks and crowd. After that, the optimizing the location of the fire unit is determined by the support of a planning tool known as ArcView. It is a Geographic Information System (GIS) through the formulation of a mathematical and accessibility model. Through the new analysis with considering the actual fact and using the technology, the results showed that to optimize of the entire range of the South Jakarta area another ten new posts o...
Minimizing Response Time with Optimal Fire Station Allocation
Studies in Engineering and Technology, 2019
Quick response time in emergency situation is critical to protect human lives. In the fast-growing cities, fire departments can fall behind the standard response time due to cities’ expansion. This research focuses on ways to improve the response time of a city’s emergency situation. A Non-linear Programming model is used to determine the locations of fire stations, so that they can cover the maximum number of residents, in terms of the geographical area and population. The model is applied to the city of Kingsville, Texas to check the practicability. The results of the research indicate that optimized locations make population coverage increment up to 15% and geographic coverage increment up to 21% with two fire stations. With three fire stations including a newly added fire station, the population coverage goes up to 48% increment and the geographic coverage increased up to 71%, which covers 88% of total city population.
Arabian Journal of Geosciences, 2020
In crowded cities, like Tehran, when a major accident occurs, such as a fire, the response from more than one fire station is usually needed at the scene. The present study focuses on demand allocation to fire stations at two ranked levels to determine the priorities of fire stations to service relevant demands. To solve this problem, this paper uses the Vector Assignment Ordered Median Problem (VAOMP), a new location-allocation model that can allocate demands to facilities at several ranked levels, based on the particular objective function. Thus, this paper uses the meta-heuristic methods of Tabu and genetic algorithms to minimize the arrival time from fire stations to demands, at two levels, at up to 5 min in the GIS environment of the 21st and 22nd districts of Tehran. The optimum parameters for each algorithm were obtained through sensitivity analysis. The results of applying the model with two algorithms in these districts with 10 existing fire stations and 336,600 inhabitants showed that the current stations are insufficient for two levels of service and that 52,840 people at level 1 and 81,320 people at level 2 have no access to services. As such, the results of two algorithms for relocation-reallocation analysis at two levels with different weightings for 13 potential and existing fire stations showed that at least 3 new stations need to be created. Furthermore, the genetic algorithm produced qualitatively superior results, in optimal values, the accuracy of allocation and timeframe, compared with the Tabu algorithm.
Determining the Locations of Potential Firefighting Teams by Using Gis Techniques
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
Wild forest fires are one of the most important disasters that affect the forest ecosystem especially in the regions with arid climate conditions. Besides, forest fires threats human life and results in seriously property loss. In order to fight forest fires effectively, it is crucial that firefighting team should reach fire location and start fire extinguishing activities within the critical response time. Since firefighting teams are transported to fire locations by fire-trucks, the optimum route with minimum travel time should be determined by considering available road network. "New Service Area" tool under "Network Analyst" extension of ArcGIS can be used to determine a region that can be reached from a point within a specified time period. In this study, it was aimed to evaluate the locations of current firefighting teams and investigate locations of potential firefighting teams using "New Service Area" tool. The study area is located in Mustafakemalpaşa in Bursa where forest lands are sensitive to forest fires at the second degree and there is currently one firefighting team in the area. The results indicated that 31.28% of forest land can be reached by current firefighting team within the critical response time. When including new firefighting teams, it was found that accessible forest lands increased to 71.55%. It can be concluded that locating new firefighting teams should be established in the study area to increase the accessible forested areas on time and GIS-based decision support systems can be effectively used to fight forest fires regarding with disaster management.
International robotics & automation journal, 2021
A general spatial fire brigade unit network density optimization problem has been solved. The distance to a particular road, from a fire station, is approximated as a continuous variable. It is proved, via integral convolution, that the probability density function of the total travel time, PDFT, is triangular. The size of the fire, when it stopped, is a function of the time it takes until the fire brigade reaches the fire location. An explicit continuous function for the expected total cost per square kilometer, based on the cost per fire station, the PDFT, the exponential fire cost function parameters, the distance between fire stations, and the speed of fire engines, is derived. It is proved that the optimal distance between fire brigade unit positions, OFD, which minimizes the total expected cost, is unique. Then, the OFDs are replaced by integers, OFDIs, for different parameter assumptions. In this process, also the optimal expected total costs are determined. It is proved that the OFD is a strictly decreasing function of the expected number of fires per area unit, a strictly increasing function of the speed of the fire engines, a strictly decreasing function of the parameters of the exponential fire cost function, and a strictly increasing function of the cost per fire station. These effects of parameter changes are also illustrated via graphs in the numerical section.
Maximum Coverage Location Model for Fire Stations with Top Corporate Risk Locations
International Journal of Industrial Engineering and Operations Management, 2021
The fire station location is a critical decision to optimize the coverage level as measured in terms of the response time. This paper focuses on optimizing the coverage problem, especially in the fire protection field, with new model features to incorporate realistic business challenges such as location criticality and secondary coverage. We extend the deterministic Maximum Coverage Location Problem to account for Top Corporate Risk locations being covered by different fire stations as primary and secondary coverage. To deal with the response time uncertainty arising in practice, we propose a new binary linear problem based on the Maximum Expected Covering Location Problem. By exploiting the model structural characteristics, we prove that the model complexity can be substantially reduced to yield an efficient solution. In the numerical experiments, we use a real case study with five years of historical data. The optimization results of the models yield a priority ranking of the fire...