An Method Relies on Penalties can Solve the Macro -and Micro Fire House Placement Issue (original) (raw)
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Fire station locations allocation
Location of fire stations is an important factor in its fire protection capability. This paper aims to determine the optimal location of fire station facilities. The proposed method is the combination of a fuzzy multi-objective programming and a genetic algorithm. The original fuzzy multiple objectives are appropriately converted to a single unified ‘min–max’ goal, which makes it easy to apply a genetic algorithm for the problem solving. Compared with the existing methods of fire station location our approach has three distinguish features: (1) considering fuzzy nature of a decision maker (DM) in the location optimization model; (2) fully considering the demands for the facilities from the areas with various fire risk categories; (3) being more understandable and practical to DM. The case study was based on the data collected from the Derbyshire fire and rescue service and used to illustrate the application of the method for the optimization of fire station locations.
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.
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.
Optimizing Fire Station Locations for the Istanbul Metropolitan Municipality
Interfaces, 2013
The Istanbul Metropolitan Municipality (IMM) seeks to determine locations for additional fire stations to build in Istanbul; its objective is to make residences and historic sites reachable by emergency vehicles within five minutes of a fire station's receipt of a service request. In this paper, we discuss our development of a mathematical model to aid IMM in determining these locations by using data retrieved from its fire incident records. We use a geographic information system to implement the model on Istanbul's road network, and solve two location models-set-covering and maximal-covering-as what-if scenarios. We discuss 10 scenarios, including the situation that existed when we initiated the project and the scenario that IMM implemented. The scenario implemented increases the city's fire station coverage from 58.6 percent to 85.9 percent, based on a five-minute response time, with an implementation plan that spans three years.
Some models for fire protection locational decisions
European Journal of Operational Research, 1980
A number of new location models which utilize the notion of coverage were developed in a study of the Baltimore City Fire Protection system. These models augment the typical analysis to include:
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...
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.
Environmental Research, Engineering and Management, 2022
Wild fires have a catastrophic impact on the environment and lead to people’s deaths. Such fires are relevant in the global context. Many countries declare some of their territories an ecological disaster zone during fires in natural ecosystems (USA, Portugal, Greece, Spain, Italy, Australia). Fires in ecosystems occurred in southern Ukraine in 2007 and in the eastern part of Ukraine in 2021, which destroyed large tracts of pine, as well as homes, buildings and caused human casualties. In the given research, much attention is paid to fire-prevention measures in natural ecosystems. It is proposed to optimize fire stations in the territory of Male Polissya (Ukraine), where frequent grass fires and grassland forest fires occur, since existing fire stations are not able to respond to all fires in the region in a timely manner due to the lack of forces and resources. Optimization of fire station locations was carried out using Voronoi diagrams. This research has a practical aspect, ensur...