Richard L. Church

Reserve selection as a maximal covering location problem

Many alternative approaches have been proposed for setting conservation priorities from a database of species (or communities) by site. We present a model based on the premise that reserve selection or site prioritization can be structured as a classic covering problem commonly used in many location problems. Specifically, we utilize a form of the maximal covering location model to identify sets of sites which represent the maximum possible representation of specific species. An example application is given for vertebrate data of Southwestern California, which is then compared to an iterative solution process used in previous studies. It is shown that the maximal covering model can quickly meet or exceed iterative models in terms of the coverage objective and automatically satisfies a complementarity objective. Refinements to the basic model are also proposed to address additional objectives such as irreplaceability and flexibility.

Identifying Critical Infrastructure: The Median and Covering Facility Interdiction Problems

Abstract Facilities and their services can be lost due to natural disasters as well as to intentional strikes, either by terrorism or an army. An intentional strike against a system is called interdiction. The geographical distribution of facilities in a supply or service system may be particularly vulnerable to interdiction, and the resulting impacts of the loss of one or more facilities may be substantial. Critical infrastructure can be defined as those elements of infrastructure that, if lost, could pose a significant threat to needed supplies (e.g., food, energy, medicines), services (e.g., police, fire, and EMS), and communication or a significant loss of service coverage or efficiency. In this article we introduce two new spatial optimization models called the r-interdiction median problem and the r-interdiction covering problem. Both models identify for a given service/supply system, that set of facilities that, if lost, would affect service delivery the most, depending upon the type of service protocol. These models can then be used to identify the most critical facility assets in a service/supply system. Results of both models applied to spatial data are also presented. Several solutions derived from these two interdiction models are presented in greater detail and demonstrate the degree to which the loss of one or more facilities disrupts system efficiencies or coverage. Recommendations for further research are also made.

A bilevel mixed-integer program for critical infrastructure protection planning

Vulnerability to sudden service disruptions due to deliberate sabotage and terrorist attacks is one of the major threats of today. In this paper, we present a bilevel formulation of the r-interdiction median problem with fortification (RIMF). RIMF identifies the most cost-effective way of allocating protective resources among the facilities of an existing but vulnerable system so that the impact of the most disruptive attack to r unprotected facilities is minimized. The model is based upon the classical p-median location model and assumes that the efficiency of the system is measured in terms of accessibility or service provision costs. In the bilevel formulation, the top level problem involves the decisions about which facilities to fortify in order to minimize the worst-case efficiency reduction due to the loss of unprotected facilities. Worst-case scenario losses are modeled in the lower-level interdiction problem. We solve the bilevel problem through an implicit enumeration (IE) algorithm, which relies on the efficient solution of the lower-level interdiction problem. Extensive computational results are reported, including comparisons with earlier results obtained by a single-level approach to the problem.

Geographical information systems and location science

Since the 1970s the field of Geographical Information Systems (GIS) has evolved into a mature research and application area involving a number of academic fields including Geography, Civil Engineering, Computer Science, Land Use Planning, and Environmental Science. GIS can support a wide range of spatial queries that can be used to support location studies. GIS will play a significant role in future location model development and application. We review existing work that forms the interface between GIS and Location Science and discuss some of the potential research areas involving both GIS and Location Science.

Modelling community evacuation vulnerability using GIS

We present a method for systematically identifying neighbourhoods that may face transportation di Yculties during an evacuation. A classi® cation of this nature o Vers a unique approach to assessing community vulnerability in regions subject to fast-moving hazards of uncertain spatial impact (e.g., urban ® restorms and toxic spills on highways). The approach is founded on an integer programming (IP) model called the critical cluster model (CCM). An heuristic algorithm is described which is capable of producing e Ycient, high-quality solu- tions to this model in a GIS context. The paper concludes with an application of the method to Santa Barbara, California.

Heuristic solution approaches to operational forest planning problems

Operational forest planning problems are typically very difficult problems to solve due to problem size and constraint structure. This paper presents three heuristic solution approaches to operational forest planning problems. We develop solution procedures based on Interchange, Simulated Annealing and Tabu search. These approaches represent new and unique solution strategies to this problem. Results are provided for applications to two actual forest planning problems and indicate that these approaches provide near optimal solutions in relatively short amounts of computer time.ZusammenfassungOperationale Forstplanungsprobleme sind typischerweise sehr schwierige Probleme, was durch die Problemgröße und durch die Struktur der „constraints“ gegeben ist. Dieser Artikelzeigt drei heuristische Lösungsansätze für operationale Forstplanungsprobleme auf. Wir haben Lösungsprozeduren entwickelt, die auf interchange, simulated annealing und Tabu-Suche basieren. Diese Ansätze stellen neue und andersartige Lösungsstrategien für dieses Problem dar. Ergebnisse bei Anwendung auf zwei tatsächliche Forstplanungsprobleme werden vorgestellt. Sie zeigen, daß diese Ansätze nahezu optimale Lösungen bei relativ kurzer Berechnungszeit liefern.

Applying simulated annealing to location-planning models

Simulated annealing is a computational approach that simulates an annealing schedule used in producing glass and metals. Originally developed by Metropolis et al. in 1953, it has since been applied to a number of integer programming problems, including the p-median location-allocation problem. However, previously reported results by Golden and Skiscim in 1986 were less than encouraging. This article addresses the design of a simulated-annealing approach for the p-median and maximal covering location problems. This design has produced very good solutions in modest amounts of computer time. Comparisons with an interchange heuristic demonstrate that simulated annealing has potential as a solution technique for solving location-planning problems and further research should be encouraged.

Measuring Accessibility for People with a Disability

This paper discusses some of the inherent problems associated with measuring accessibility for people on a landscape of surfaces, barriers, and travel modes. Along with this discussion we propose a new perspective for measuring accessibility with a focus on people with differing abilities. Even though our focus is on people with a physical disability, such an approach can be easily extended and is able to be generalized to other needs and differences. Traditional measurements of accessibility are flawed, as they fail to directly account for mobility and physical differences among people. They ignore structural barriers and individual mobility limitations that affect travel time, effort, and even successful completion. To make sense of this dilemma, we propose an accessibility measurement framework that includes measures of absolute access, gross access, closest assignment access, single and multiple activity access, probabilistic choice access, and relative access. Most of these measures of access have been proposed by others, but our framework attempts to codify an approach that helps to overcome weaknesses in using only the absolute access measurement currently used in ADA compliance. Such measures can be used to map accessibility as well as to help select the mitigation or renovation projects that yield the greatest increase in accessibility for people with disabilities. We argue that for many urban and building design problems providing absolute access for people with physical disabilities should be accompanied by the use of a relative access measurement, so that removing barriers can be done in the order that provides the greatest improvement in access for a given level of expenditure.

Spatial optimization as a generative technique for sustainable multiobjective land-use allocation

In this paper, we examine the applicability of spatial optimization as a generative modelling technique for sustainable land‐use allocation. Specifically, we test whether spatial optimization can be used to generate a number of compromise spatial alternatives that are both feasible and different from each other. We present a new spatial multiobjective optimization model, which encourages efficient utilization of urban space through infill development, compatibility of adjacent land uses, and defensible redevelopment. The model uses a density‐based design constraint developed by the authors. The constraint imposes a predefined level of consistent neighbourhood development to promote contiguity and compactness of urban areas. First, the model is tested on a hypothetical example. Further, we demonstrate a real‐world application of the model to land‐use planning in Chelan, a small environmental amenity town in the north‐central region of the State of Washington, USA. The results indicate that spatial optimization is a promising method for generating land‐use alternatives for further consideration in spatial decision‐making.

Mapping transit-based access: integrating GIS, routes and schedules

Accessibility is a concept that is not entirely easy to define. Gould (1969) once stated that it is a ‘slippery notion … one of those common terms that everyone uses until faced with the problem of defining and measuring it’. Considerable research over the last 40 years has been devoted to defining and measuring accessibility, ranging from access to jobs within an hours travel time to the ease at which given places can be reached. This article is concerned with the measurement of access provided by transit. It includes a review of past work on measuring accessibility in general and with respect to transit services in particular. From this overview of the literature, it can be seen that current methods fall short in measuring transit service access in several meaningful aspects. Based on this review and critique, we propose new refinements that can be used to help overcome some of these shortcomings. As a part of this, we define an extended GIS data structure to handle temporal elements of transit service. To demonstrate the value of these new measures, examples are presented with respect to mapping accessibility of transit services in Santa Barbara, California. Finally, we show how these measures can be used to develop a framework for supporting transit service analysis and planning.