Applications of Location Analysis

In recent years, technology has improved and distribution channels such as credit cards, telephone-internet banking, Automated Teller Machines (ATMs) etc. have become alternative opportunities for reaching services of banks. However, banks generally gain new customers and develop customers’ loyalty at their branches. Since branches are the indispensable contact points between the banks and their customers, no bank can easily avoid opening new branches or reorganizing the locations of current ones. According to the current statistics of The Banks Association of Turkey, the number of total bank branches has increased by 5.35 % from 10,450 to 11,009 in the last year. According to the statistics of Retail Banker International, JPMorgan & Chase opened 89 new branches in June 2013, which increased number of its branches from 5,608 to 5,697. In the same period, BB&T increased the number of its branches from 1,775 to 1,851 (Retail Banker International 2013). This shows that, due to the effects of increase in total population, population per bank branch and individual earnings, banks try to increase the number of their branches by locating them in the right places. Therefore, the branch location problem is a fundamental topic for banks in reaching their strategic goals.

This case study highlights issues that are faced by location theorists in solving real-world problems by drawing upon a project involving the location of a Logistics Park in the Southeastern region of North Carolina, USA. First, the location modelling is presented using standard analytical methodology from location theory. Thereafter, a structured framework, referred to by its acronym SIRC, is introduced, which can be used for real-life location modeling problems. The implementation of SIRC is then illustrated through a description of the actual process used during the implementation of the project. Finally, the case study closes with its most important section, namely, lessons learned from the project that can guide future academic research in location theory in incorporating real life factors into location modeling.

Forestry is the natural resource industry most dominated by spatial considerations. Forests are an extensive resource typically spread out over millions of hectares. In this paper we focus on the industrial aspects of forestry, and some location issues that flow from these. This is in contrast to a focus on location analysis and then asking about its applications in forestry.

In general, layout planning problems can be classified as in-house location problems where the aim is to minimize the total pairwise communication or material handling costs based on distances by deciding on the relative positions of any kind of organizational units inside a building. In this chapter the focus is on a hospital layout planning problem where 25 organizational units have to be located on 6 levels of a hospital building. In order to solve the problem, a graph-theoretical approach is applied using real-world data. Furthermore, the idea of an iterative simulation-optimization approach is presented.

Modeling useful habitat can be a daunting task, especially for territorial species. The classic approach is to develop a wildlife habitat relationship model (WHR) that can be used to predict the presence of a specific animal based upon the geographic distribution of needed habitat elements, which may vary with season and vary when they are raising offspring. For example, the State of California main-tains a geographic database that depicts the possible presence and suitability of 694 terrestrial vertebrates based upon the application of WHR models to geographic data. Conservation planners often estimate the carrying capacity of a habitat for a territorial species by first estimating the total area of suitable habitat and then divid-ing that estimate by the average size of a given territory. Such estimates are approx-imate at best given that suitable habitat is often distributed unevenly across a land-scape. This chapter presents an application of a location model as a means to gen-erate a more accurate estimate of the carrying capacity of a territorial species in the forests of California.

Wildfire is a natural process which can lead to a variety of conditions in a forested landscape, some quite destructive. Whatever the cause of a fire, no one questions that destructive fires often occur during certain weather events where litter (woody debris from trees) and ladder fuels are abundant. The US Forest Service has implemented a program to reduce litter and ladder fuels along with thinning of stands in order to mitigate the extent and severity of fires, especially in areas surrounding critical habitat. Fuels reduction/treatment plans are expensive and therefore must be planned over a period of years, often two decades or more. This chapter presents an application of a location-scheduling model which has been developed for the US Forest Service to determine when and where fuels treatments are to be implemented. The model itself is an integer linear programming problem, which has been embedded in a decision support system called iFASST. This modeling system is quite flexible, and because of its flexibility has now been used in many of the National Forests in California.

Health conditions are much easier to prevent than to treat, and recovery is often more likely if an illness is diagnosed at an early stage. The substantial savings in the costs of diagnosis and therapy as well as the relatively lower capital investment associated with preventive care programs have been recognized for a long time. Preventive care programs can save lives and contribute to a better quality of life by reducing the needs for radical treatments. For example, there is evidence that mammograms taken on a regular basis have the potential to reduce deaths from breast cancer for women between the ages of 50 and 69 by up to 40 %.

There is a substantial theoretical literature on the location of retail facilities in space assuming that the spatial demand curve is known, or that the ideal data needed to estimate such a curve is available. This study shows how to implement a formal location analysis for a retail activity (postal services) when all that is known is revenue of currently operating facilities. Further complications, such as the delivery of retail services through two different types of outlets are also accommodated by the method. In the end, it is possible to implement a formal business model for the delivery of retail postal services that allows the user to simulate the consequences of dramatic changes in the way that those services are supplied to the public.

Optimizing school location can dramatically improve the quality of life of a large number of children, especially of those in rural areas in developing countries. Moreover, when transportation costs are considered, improving the location and assignment of student to schools can save important resources that can be used to provide better teaching supplies to the students. We review selected literature on school location and present an application in Brazil as well as overview some experiences in Chile.

Fire protection and emergency response is a critical public service provided to communities. The importance of first responders is without question, saving lives, protecting property, preserving the environment and antiquities, and ensuring general safety and security. These services, however, are not cheap, often consuming a significant portion of a community’s annual budget. Associated costs for fire protection include building stations (and acquiring property), equipment, maintenance and staffing. Good planning and administrative oversight is therefore essential, especially given financial hardships faced by all communities and local governments. Such management includes anticipating future needs and deciding where new fire stations should be sited, but also reassessment of existing stations relative to changing demands for service. This chapter details issues of fire protection in a city in California experiencing sustained population growth and urban development. A location planning model is applied to support long term, cost effective fire station response through the siting of new facilities combined with strategic changes to the existing system.

The problem of optimally locating sensors on a traffic network has been object of growing interest in the past few years. Sensor location decisions models differ from each other according to the type of sensors that are to be located and the objective that one would like to optimize. In this paper, we survey the main existing contributions in the literature related to the optimal location strategies of Automatic Vehicle Identification (AVI) readers on the links of a network to get travel time information.

Districting is a classic design problem when attempting to provide an efficient service to a geographically dispersed demand. There exists a natural trade-off between aggregation, which allows the pooling of resources, and individualization, where each individual demand has its own resources and response is as efficient as possible. Police and security providers are no strangers to this phenomenon. Having a single set of resources to satisfy the demand over an entire service area avoids the duplication of resources, coordination problems, and uneven workloads that can occur in districting. However, when the service area is large, service times at certain locations can exceed acceptable levels, making it more attractive to service this demand from distributed resources. Furthermore, districting allows for specialization of the resources to efficiently service a diverse demand in different areas. Such specialization causes additional complexity if managed from a centralized pool of resources. This creates the basic problem of separating a demand area into subregions to organize the service process.

We present a case of location and sizing of a number of new jails, capacity increasing of existing jails, and inmate allocation to them, in Chile. The main criteria are the cost and the distances between the jails and courts, as well as the maximum distance that relative and other visitors have to travel to visit the inmates. The capacities of the jails range from a few inmates to 2,000 people, composed by pre-trial detainees, defendants under trial and convicted offenders. Different categories of inmates stay in the system for very different times, going from a few days to life sentences. Some percentage of overcrowding is permitted, and penalized.

The procedure utilizes an exact mathematical programming formulation for the whole country. Different scenarios of jail population growth are developed and used separately to assess the required capacities and locations. A minimum regret analysis is applied finally, to find an adequate solution no matter what is the actual scenario.

The location-allocation problem serves to deploy assets effectively to respond to a known or estimated geographically distributed demand for service, including providing emergency services. At first glance, the rescue vessel location problem in the Search and Rescue (SAR) domain is similar to the emergency vehicle location problem such as for ambulance location. In both cases, mathematical location models can be formulated to maximize the number of incidents that can be serviced by a specified number of resources (vehicles) within a pre-specified amount of time, or, alternatively, we can minimize the time it would take a vehicle to arrive at the scene of the incident. However, several differences exist. First of all, in the case of emergency vehicle location, all response units are generally assumed to have the same capability and speed. Conversely, the Canadian Coast Guard (CCG) has many different SAR rescue vessel types that were designed or purchased with specific tasks in mind, and not all are equally effective at handling different incident types. Also, the ranges vary greatly among different types of rescue vessels, so rescue vessel capabilities need to be considered in our study. Furthermore, the method of computing distances to the incidents is different as rescue vessels are patrolling on the sea, thus requiring a land-avoidance algorithm to calculate the travel distance rather than Euclidean or Manhattan distance metrics. However, land-avoidance distance is calculated before performing the optimization in this study, so this distinction is moot in this instance.

Over time, the decision-making needs of military commanders have had a strong influence upon the development of the field of operations research and analytic problem solving. The challenge of correctly positioning military units and resources within a geographical setting has vexed commanders and their staffs for thousands of years. However, it is only in the last 70 years that optimization methods have developed to the point where analysts can apply them to accomplish such goals. Along the way toward solving these narrowly defined military-focused problems, the advancement of the field has benefitted as generalizable techniques are extended beyond their origins to countless non-military applications. For example, military analysts first solved complex problems regarding routes for convoys of ships, code breaking, and materiel allocation mathematically during World War II ultimately leading to the development of linear and mathematical programming techniques by wartime scientists. Location analysis knowledge was similarly benefitted by the war, as commanders required the ability to spatially position munitions to destroy a target and covering a search area to find the enemy. The benefit is reciprocal however, as military strategy and planning since World War II have literally been redefined by the operations research field’s ability to solve larger and more complex problems.