Location models in the public sector

The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.Location analysis, public facilities, covering models

Modular Capacitated Maximal Covering Location Problem for the Optimal Siting of Emergency Vehicles

To improve the application of the maximal covering location problem (MCLP), several capacitated MCLP models were proposed to consider the capacity limits of facilities. However, most of these models assume only one fixed capacity level for the facility at each potential site. This assumption may limit the application of the capacitated MCLP. In this article, a modular capacitated maximal covering location problem (MCMCLP) is proposed and formulated to allow several possible capacity levels for the facility at each potential site. To optimally site emergency vehicles, this new model also considers allocations of the demands beyond the service covering standard. Two situations of the model are discussed: the MCMCLP-facility-constraint (FC), which fixes the total number of facilities to be located, and the MCMCLP-non-facility-constraint (NFC), which does not. In addition to the model formulations, one important aspect of location modeling—spatial demand representation—is included in the analysis and discussion. As an example, the MCMCLP is applied with Geographic Information System (GIS) and optimization software packages to optimally site ambulances for the Emergency Medical Services (EMS) Region 10 in the State of Georgia. The limitations of the model are also discussed

Location optimization of urban fire stations: access and service coverage

Fire and rescue services are among the most critical public services provided by governments to protect people, property and the environment from fires and other emergencies. Efficient deployment of fire stations is essential to ensure timely response to calls for service. Given the geographic nature of such problems, spatial optimization approaches have long been employed in public facility location modeling along these lines. In particular, median and coverage approaches have been widely adopted to help achieve travel-cost and service-coverage goals, respectively. This paper proposes a bi-objective spatial optimization model that integrates coverage and median goals in the service of demand areas. Based on the properties of derived objective functions, we presented a constraint-based solution procedure to generate the Pareto frontier, enabling the identification of alternative fire station siting scenarios. The developed model is applied to an empirical study that seeks to identify the best fire station locations in Nanjing, China. The results demonstrate the value of spatial optimization in assisting fire station planning and rescue resource deployment, highlighting important policy implications

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

Optimal Siting of Park and Ride Facilities Using Geospatial Approach

الزيادة المستمرة في ملكية السيارات هي واحدة من الاسباب الرئيسية في الاختناقات المروربة حول العالم وخصوصا في مراكز المدن، محطات الركن والركوب هو احدى الوسائل التي تمكن مستخدمي السيارات الخاصة لركن سيارتهم في الاماكن مخصصة لها ومن ثم استخدام وسائل النقل العام لغرض اكمال رحلاتهم دون ان يتسبب ذلك في الاختناقات المرورية، في هذا البحث ركزنا على تشخيص اهم العوامل التي تحدد هذه المحطات كالطلب على النقل وتوفر الطرق الرئيسية وتوفر المساحة المناسبة لها، بعد ذلك استخدمنا عملية التحليل الهرمي (AHP) لغرض معرفة تاثير كل عامل على تلك المحطات ومن ثم ادراج تلك العوامل مع مدى تأثيرها في برنامج الـGIS لتحديد الاماكن المناسبة لتلك المحطات.The significant increase in car ownership has been recognized as one of the main reasons for traffic congestion worldwide, especially in city centers. Park-and-ride (P&R) facilities, which are car parks where users can adjust to public transportation to carry on their journeys, have long been used as an effective solution to mitigate congestion issues without affecting traffic demand. However, literature on the optimal localization of these facilities using geospatial approaches are still emerging. Feasible locations of P&R facilities are of crucial importance not only for users but also to local authorities and the environment. The aim of this paper is to explore the significance of several factors affecting optimal locations of P&R using Analytic Hierarchy Process (AHP) and to propose a multi-criteria geospatial approach to locate optimal park and ride facilities in Karbala, Iraq. Three key aspects are tested in the localization process, including users’ coverage, accessibility to major roads, and area availability using Geospatial Tool. The case study on the holy city of Karbala in Iraq was implemented and the results show that the optimization model is proved to be powerful in providing more optimal locations of P&R facilities. The paper concludes with a discussion of the practical implications, research limitations and future research directions

Enhancing Equity in Public Transportation Using Geographic Information Systems and Spatial Optimization

Public transportation is a vital part of urban living. For instance, public transportation services help reduce road congestion, oil consumption and air pollution, and they serve people who need to travel throughout urban environments at the same time do not have access to private vehicles. The latter aspect is an important matter of social justice. Therefore, it is important to understand why the interest in equity in transport is growing, why public transportation should favor the transport disadvantaged, and why analyses of equity measurement and improvement are needed. Measuring the level of access to public transportation among the transport disadvantaged provides a theoretical basis for analyzing potential improvements in access by adjusting public transportation facility locations. This research will focus on modeling approaches used in establishing public transportation infrastructure and systems. Using GIS and spatial optimization models, the level of access to public transportation in terms of equity will be evaluated and improvement of the level of access will be attempted by offering new service stop locations. To this end, using the Maximal Covering Location Problem (MCLP), the optimal locations of potential facilities to cover equity favoring origin- and destination-based demand are identified. This research finally provides a set of optimal service stop locations maximizing coverage of origin- and destination-based demand simultaneously through implementation of a bi-objective model, applied to the City of Hilliard, Ohio

Quantifying Resiliency Risk Metrics through Facility Dispersion

During the last century, airbases were attacked at least 26 times in an effort to destroy the enemy at its base. Attacks on military airbases impose prohibitive losses to critical infrastructure, which in turn impacts the maintenance of air power projection. The primary enemy threat facing critical infrastructure today is the use of ballistic and land-attack cruise missiles to disrupt an airbase’s ability to launch and recover aircraft. Over the last decade, ballistic and cruise missile technology has grown to allow the world’s most powerful countries to achieve a nascent threat to forward operating bases used in theater security campaigns worldwide. Planners can reduce the impact of ballistic and cruise missile attacks on aircraft projection platforms by incorporating a number of resiliency measures, including dispersal of critical infrastructure assets, such as aircraft fuel containment and conveyance equipment. The integration of resiliency measures increases construction costs; therefore, planners need to identify an optimum balance between maximizing airbase resiliency and minimizing site costs. This research presents an airbase resiliency assessment capable of quantifying facility dispersal and risk tolerance levels in an environment threatened by missile attack. Model performance was evaluated using a case study from Osan AB, Republic of Korea. The model’s distinctive capabilities are expected to support planners in the critical task of analyzing and selecting the design strategy that maximizes airbase resiliency against the threat of ballistic and cruise missile attack

Hierarchical location-allocation models for congested systems

In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and their locations that will cover a given region with a distance or time standard. The second model is cast as a Maximal Covering Location formulation. A heuristic procedure is then presented together with computational experience. Finally, some extensions of these models that address other types of spatial configurations are offered.Hierarchical location, congestion, queueing