Fire station location selection for İstanbul

Makale Endüstri Mühendisliği dergisinin "YA/EM 2009 özel sayısı"nda yayımlanmıştır.Özellikle acil hizmetler veren polis, hastane, itfaiye gibi kurumlar için yer seçimi büyük önem taşımaktadır. Uygun bir yer seçimi gerçekleştirilmediği takdirde bunun sonuçları insan hayatını tehlikeye atabilir niteliktedir. İstanbul gibi büyük metropollerde, artan nüfus ve trafik yoğunluğunun yanı sıra bir de metropolün deprem kuşağında olması durumunda, itfaiye araçlarının olay yerine en hızlı şekilde ulaşması hayati önem taşımakta; bu da itfaiye istasyonu yerinin etkin seçimine kritik bir rol yüklemektedir. Bu çalışma; İstanbul Büyükşehir Belediyesi tarafından kararlaştırıldığı gibi, itfaiye teşkilatının her bölgeye en çok beş dakikada erişebilmesi ve kapsama alanının %100 olması hedeflenerek yeni kurulacak olan itfaiye istasyonlarının küme kapsama modeli yardımıyla konumlandırılmasını içermektedir. Bu amaçla bir tamsayı programlama modeli kurulmuş, coğrafi bilgi sistemlerinden elde edilen verilerle model çözülmüş, seçilen yerler için itfaiye kurulması durumunda yangın hizmet düzeyinin değişimi incelenmiştir.For emergency services such as ambulance systems and fire departments, location selection plays a critical role due to the direct impact of these services on human lives. Timeliness plays a primary role in location selection decision of fire stations for large metropolitan cities such as Istanbul with increasing population with a high level of congestion coupled with an imminent earthquake risk. This study is based on a set-covering model for locating new fire stations, which target to serve each area at most in five minutes and improve their coverage area to 100% for Istanbul Municipality Fire Department. Accordingly, a set-covering model is built and solved using the data retrieved from geographical information systems. Finally the change in service level with proposed fire station locations is investigated and further suggestions are provided

İstanbul`da itfaiye istasyonu yerlerinin seçimi için yeni bir model - Fire station location selection for Istanbul

This Article is in Turkish and can be accessed from the link below.Özellikle acil hizmetler veren polis, hastane, itfaiye gibi kurumlar için yer seçimi büyük önem taşımaktadır. Uygun bir yer seçimi gerçekleştirilmediği takdirde bunun sonuçları insan hayatını tehlikeye atabilir niteliktedir. İstanbul gibi büyük metropollerde, artan nüfus ve trafik yoğunluğunun yanı sıra bir de metropolün deprem kuşağında olması durumunda, itfaiye araçlarının olay yerine en hızlı şekilde ulaşması hayati önem taşımakta; bu da itfaiye istasyonu yerinin etkin seçimine kritik bir rol yüklemektedir. Bu çalışma; İstanbul Büyükşehir Belediyesi tarafından kararlaştırıldığı gibi, itfaiye teşkilatının her bölgeye en çok beş dakikada erişebilmesi ve kapsama alanının %100 olması hedeflenerek yeni kurulacak olan itfaiye istasyonlarının küme kapsama modeli yardımıyla konumlandırılmasını içermektedir. Bu amaçla bir tamsayı programlama modeli kurulmuş, coğrafi bilgi sistemlerinden elde edilen verilerle model çözülmüş, seçilen yerler için itfaiye kurulması durumunda yangın hizmet düzeyinin değişimi incelenmiştir. - For emergency services such as ambulance systems and fire departments, location selection plays a critical role due to the direct impact of these services on human lives. Timeliness plays a primary role in location selection decision of fire stations for large metropolitan cities such as Istanbul with increasing population with a high level of congestion coupled with an imminent earthquake risk. This study is based on a set-covering model for locating new fire stations, which target to serve each area at most in five minutes and improve their coverage area to 100% for Istanbul Municipality Fire Department. Accordingly, a set-covering model is built and solved using the data retrieved from geographical information systems. Finally the change in service level with proposed fire station locations is investigated and further suggestions are provided

Optimizing fire station locations for the Istanbul metropolitan municipality

Copyright @ 2013 INFORMSThe 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

Optimizing fire station locations for the Istanbul metropolitan municipality

Copyright @ 2013 INFORMSThe 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

Dynamic routing model and solution methods for fleet management with mobile technologies

Author name used in this publication: K. L. ChoyAuthor name used in this publication: Wenzhong Shi2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms

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. © 2006 Elsevier B.V. All rights reserved

Optimisation of speed camera locations using genetic algorithm and pattern search

Road traffic accidents continue to be a public health problem and are a global issue due to the huge financial burden they place on families and society as a whole. Speed has been identified as a major contributor to the severity of traffic accidents and there is the need for better speed management if road traffic accidents are to be reduced. Over the years various measures have been implemented to manage vehicle speeds. The use of speed cameras and vehicle activated signs in recent times has contributed to the reduction of vehicle speeds to various extents. Speed cameras use punitive measures whereas vehicle activated signs do not so their use depends on various factors. Engineers, planners and decision makers responsible for determining the best place to mount a speed camera or vehicle activated sign along a road have based their decision on experience, site characteristics and available guidelines (Department for Transport, 2007; Department for Transport, 2006; Department for Transport, 2003). These decisions can be subjective and indications are that a more formal and directed approach aimed at bringing these available guidelines together in a model will be beneficial in making the right decision as to where to place a speed camera or vehicle activated sign is to be made. The use of optimisation techniques have been applied in other areas of research but this has been clearly absent in the Transport Safety sector. This research aims to contribute to speed reduction by developing a model to help decision makers determine the optimum location for a speed control device. In order to achieve this, the first study involved the development of an Empirical Bayes Negative Binomial regression accident prediction model to predict the number of fatal and serious accidents combined and the number of slight accidents. The accident prediction model that was used explored the effect of certain geometric and traffic characteristics on the effect of the severity of road traffic accident numbers on selected A-roads within the Nottinghamshire and Leicestershire regions of United Kingdom. On A-roads some model variables (n=10) were found to be statistically significant for slight accidents and (n=6) for fatal and serious accidents. The next study used the accident prediction model developed in two optimisation techniques to help predict the optimal location for speed cameras or vehicle activated signs. Pattern Search and Genetic Algorithms were the two main types of optimisation techniques utilised in this thesis. The results show that the two methods did produce similar results in some instances but different in others. Optimised results were compared to some existing sites with speed cameras some of the results obtained from the optimisation techniques used were within proximity of about 160m. A validation method was applied to the genetic algorithm and pattern search optimisation methods. The pattern search method was found to be more consistent than the genetic algorithm method. Genetic algorithm results produced slightly different results at validation in comparison with the initial results. T-test results show a significant difference in the function values for the validated genetic algorithm (M= 607649.34, SD= 1055520.75) and the validated pattern search function values (M= 2.06, SD= 1.17) under the condition t (79) = 5.15, p=0.000. There is a role that optimisation techniques can play in helping to determine the optimum location for a speed camera or vehicle activated sign based on a set of objectives and specified constraints. The research findings as a whole show that speed cameras and vehicle activated signs are an effective speed management tool. Their deployment however needs to be carefully considered by engineers, planners and decision makers so as to achieve the required level of effectiveness. The use of optimisation techniques which has been generally absent in the Transport Safety sector has been shown in this thesis to have the potential to contribute to improve speed management. There is however no doubt that this research will stimulate interest in this rather new but high potential area of Transport Safety