Richard Church

A relative access measure to identify barriers to efficient transit use by persons with visual impairments

Disability and Rehabilitation, 2005

Purpose. Persons with visual impairments or blindness can face significant restrictions to their ... more Purpose. Persons with visual impairments or blindness can face significant restrictions to their efficient travel, especially when attempting transit transfers and using a large, multi-modal terminal. Little is known about what makes some tasks much harder than others. This paper presents an approach to empirically measure the difficulty of a variety of transit tasks. Method. An experiment was conducted at an urban transit terminal, with three other transit modes nearby. Thirty persons with visual impairments attempted to make five simulated transfers between these modes. Errors and time to complete these tasks were collected in order to quantify the nature of various barriers to efficient travel for this group. In total, 20 locations were visited. Completion times were compared to a sighted traveler to determine a measure of the time penalty, or 'relative access measure.' Results. Two basic findings are reported. Empirical data showed that different types of transit tasks and locations had a wide range of difficulty and inherent time penalties. Some tasks like crossing a difficult street, finding unmarked track doors, and finding inconsistently placed amenities were quite time consuming and sometimes impossible to accomplish. Other tasks, like walking to a street corner and crossing a simpler street, had much lower penalties and could be completed with ease. Conclusions. The placement of additional cues, those of identity and direction, provided with auditory signage, were able to eliminate much of the uncertainty and time restrictions associates with transit use and navigation for persons with visual impairments.

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Measuring Accessibility for People with a Disability

by Richard Church and Jim Marston

Geographical Analysis, 2003

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Finding shortest paths on real road networks: the case for A*

International Journal of Geographical Information Science, Apr 1, 2009

The problem of identifying the shortest path along a road network is a fundamental problem in net... more The problem of identifying the shortest path along a road network is a fundamental problem in network analysis, ranging from route guidance in a navigation system to solving spatial allocation problems. Since this type of problem is solved so frequently, it is important to craft an approach that is as efficient as possible. Based upon past research it is generally accepted that several efficient implementations of the Dijkstra algorithm are the fastest at optimally solving the 'one-to-one' shortest path problem . We show that the most efficient, state-of-the-art implementations of Dijkstra can be improved by taking advantage of network properties associated with GIS-sourced data. The results of this paper, derived from tests of different algorithmic approaches on real road networks, will be extremely valuable for application developers and researchers in the GIS community.

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Business Site Selection, Location Analysis and GIS

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Integrating Normative Location Models into GIS: Problems and Prospects with the p-median Model (94-5) - eScholarship

There has been considerable interest in the development of analysis techniques for Geographical I... more There has been considerable interest in the development of analysis techniques for Geographical Information Systems (GIS). This includes such normative spatial models as vehicle routing models, districting and turfing models for dividing up land into territories for schools, sales/service, and voting, and location models for identifying sites or patterns of sites to provide service accessibility. The GIS system may provide a unique data base for application and analysis. This paper discusses several problems associated with the integration of a normative location model into a GIS. A number of specifics associated with the p-median model are given. These include: demand zone definition, facility site definition, and solution algorithm selection and development. Within the context of selecting a solution process, we show that such a selection is not necessarily an easy one to make. We demonstrate that the best such solution technique may have some potential drawbacks in application. We present the results of several test applications and a glimpse of the pathology of the final solutions. This discussion raises a major, but often ignored, issue involving the application of a location heuristic: namely, how often should we restart a heuristic to help ensure that the best solution found is optimal or near-optimal. We propose and test a dynamic stopping rule that can be used to help ensure that the best solution is identified. The results of this analysis can be of great, practical value in the successful application of location models within a GIS framework.

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National Center for Geographic Information and Analysis A Comparison of Strategies for Data Storage Reduction in Location-Allocation Problems

Many solution techniques for discrete location-allocation problems make use of a sorted distance ... more Many solution techniques for discrete location-allocation problems make use of a sorted distance strings data structure in order to speed processing time. Such data structures are commonly used, for example, within interchange heuristics and lagrangian relaxation codes. The primary drawback to distance strings is that in a standard computer architecture they require approximately 50% additional memory storage in comparison to a standard distance matrix. This is due to the fact that distance strings must store not only distances, but also the order of the nodes sorted by increasing distance. To reduce the additional memory requirements of distance strings, researchers such as Hillsman [1980] and Densham and Rushton [1992a] have proposed a strategy for cutting the distance strings to include only sets of relatively close neighbor nodes. This has become an important implementation issue for solving relatively large locationallocation problems. In fact, the new Location-Allocation module of the ARC/Info GIS system uses a distance string structure and a string cutoff option to save storage and processing time. The danger in employing only partial distance strings is that if too few distance entries are stored in the distance strings, heuristic or algorithmic performance may be compromised in that the quality of the solutions generated may be less than desirable. This paper tests the effects on solution quality of imposing different distance string definitions and sizes. The goal is to establish guidelines concerning the degree to which the distance strings data structure may be reduced for memory savings without adversely affecting solution quality. The paper proposes and compares two alternative methods to that of Hillsman and of Densham and Rushton for the selection of nodes to be included within the distance strings data structure. We show that the two new alternative methods for defining distance strings appear to outperform the earlier approach. The results of this paper can be used to aid users in determining the extent that distance string cutoffs should be employed in application as well as aid in the development of location modeling software.

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The Basic Organizing/Optimizing Training Scheduler (BOOTS): User's Guide. Technical Report 151

This report provides the step-by-step instructions required for using 'the Navy's Basic Organizin... more This report provides the step-by-step instructions required for using 'the Navy's Basic Organizing/Optimizing Training Scheduler (BOOTS) s stem. BOOTS is a computerized tool designed to aid in the creation of master training schedules for each Navy recruit training command. The system is defined in terms of three major. functions: (1) data file editing, in which the user defines the scheduling parameters and constraints, (2) scheduling, in which the user builds the training schedule while using the system to monitor all of the defined constraints, and (3) data output generators for formatting and printing hard copies of the resulting schedule and documenting the supporting data files. Following an introduction (section 1)-, the guide contains three sections and two appendixes. Section 2 provides a general description'of the master training scheduling problem. A brief overview of BOOTS is provided in section 3. This is followed in section 4 by detailed step-by-step instructions on how to use the BOOTS systeM to prepare new and/or revise old master training schedules. An annotated list of the BOOTS software and detailed specifications of the hardware configuration requirements needed by the BOOTS system are contained in appendixes to the guide. (Author/KC)

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A Comparison of Strategies for Data Storage Reduction in Location-Allocation Problems (95-4)

Many solution techniques for discrete location-allocation problems make use of a sorted distance ... more Many solution techniques for discrete location-allocation problems make use of a sorted distance strings data structure in order to speed processing time. Such data structures are commonly used, for example, within interchange heuristics and lagrangian relaxation codes. The primary drawback to distance strings is that in a standard computer architecture they require approximately 50% additional memory storage in comparison to a standard distance matrix. This is due to the fact that distance strings must store not only distances, but also the order of the nodes sorted by increasing distance. To reduce the additional memory requirements of distance strings, researchers such as Hillsman [1980] and Densham and Rushton [1992a] have proposed a strategy for cutting the distance strings to include only sets of relatively close neighbor nodes. This has become an important implementation issue for solving relatively large locationallocation problems. In fact, the new Location-Allocation module of the ARC/Info GIS system uses a distance string structure and a string cutoff option to save storage and processing time. The danger in employing only partial distance strings is that if too few distance entries are stored in the distance strings, heuristic or algorithmic performance may be compromised in that the quality of the solutions generated may be less than desirable. This paper tests the effects on solution quality of imposing different distance string definitions and sizes. The goal is to establish guidelines concerning the degree to which the distance strings data structure may be reduced for memory savings without adversely affecting solution quality. The paper proposes and compares two alternative methods to that of Hillsman and of Densham and Rushton for the selection of nodes to be included within the distance strings data structure. We show that the two new alternative methods for defining distance strings appear to outperform the earlier approach. The results of this paper can be used to aid users in determining the extent that distance string cutoffs should be employed in application as well as aid in the development of location modeling software.

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Integrating Normative Location Models into GIS: Problems and Prospects with the p-median Model (94-5)

There has been considerable interest in the development of analysis techniques for Geographical I... more There has been considerable interest in the development of analysis techniques for Geographical Information Systems (GIS). This includes such normative spatial models as vehicle routing models, districting and turfing models for dividing up land into territories for schools, sales/service, and voting, and location models for identifying sites or patterns of sites to provide service accessibility. The GIS system may provide a unique data base for application and analysis. This paper discusses several problems associated with the integration of a normative location model into a GIS. A number of specifics associated with the p-median model are given. These include: demand zone definition, facility site definition, and solution algorithm selection and development. Within the context of selecting a solution process, we show that such a selection is not necessarily an easy one to make. We demonstrate that the best such solution technique may have some potential drawbacks in application. We present the results of several test applications and a glimpse of the pathology of the final solutions. This discussion raises a major, but often ignored, issue involving the application of a location heuristic: namely, how often should we restart a heuristic to help ensure that the best solution found is optimal or near-optimal. We propose and test a dynamic stopping rule that can be used to help ensure that the best solution is identified. The results of this analysis can be of great, practical value in the successful application of location models within a GIS framework.

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Capture, Capacities, and Thresholds

Location Covering Models, 2018

There can be a number of different problem settings under which covering models can be defined an... more There can be a number of different problem settings under which covering models can be defined and applied. Many of the models that are discussed in this chapter were originally inspired by issues associated with retail and competition. Although one at first blush may think of retail siting and coverage models as having little in common, except for something obvious like a pizza chain attempting to locate facilities so that it can deliver pizzas everywhere in a city within 30 min, there are surprisingly many retail elements that can be defined and addressed using coverage constructs.

Analysing cliques for imposing adjacency restrictions in forest models

Forest Science, 1996

Location Modeling and Covering Metrics

Location Covering Models, 2018

The field of location science is firmly rooted in several substantive developments, including the... more The field of location science is firmly rooted in several substantive developments, including the ground-breaking work of von Thunen (1826), Launhardt (1872), Weber (1909), Hotelling (1929), Hoover (1948, 1967), Christaller (1933), Losch (1954), Weiszfeld (1937), Isard (1956), Moses (1958), Cooper (1963, 1964), Manne (1964), Hakimi (1964, 1965), Buffa et al. (1964) and Toregas et al. (1971). These authors may be considered founding fathers of location science, and they dealt with problems involving the competitive uses of land and land allocation, the location of industrial and communication facilities, the spatial arrangement of retail centers across a landscape, the location of competitors and competition through pricing, the layout of factory space, and the early use of computers in structuring and solving location problems. Since these early contributions, the field has expanded into new areas of application, new theoretical models, specialized solution approaches, and conceptual/technical forms of modeling location decisions and representing the spatial domain within Geographical Information Systems (GIS). Finally, as the field of location science has matured so too have the applications in both the public and private sectors.

Drone service response: Spatiotemporal heterogeneity implications

Journal of Transport Geography, 2021

Single facility siting involving allocation decisions

European Journal of Operational Research, 2020

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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The Nested Hierarchical Median Facility Location Model

INFOR: Information Systems and Operational Research, 1991

In this paper we deal with the location of nested hierarchical facilities. In hierarchical facili... more In this paper we deal with the location of nested hierarchical facilities. In hierarchical facilify systems there are multiple levels of service facilities such that each facilify level provides different but related services. The specific hierarchical locational system which we model is a nested facilify hierarchy such that the location of a higher level facilify at a site requires that services of all lower levels also be located at that site. In addition, it is assumed that all demand is serviced directly by the closest facilify ofthe appropriate level and that there are no referrals. We formulate the nested hierarchical median problem as a binary linear program (BLP). The resulting BLPs can be solved with a Lagrangian dual bounding approach based on a novel extension of the corresponding p-median solution procedure and a special relaxation of the BLP formulation. Computational experience for 2-level and 3-level locational systems on moderately sized networks are reported. Dans cet article, nous traitons de la localisation de facilites hierarchiquement dependantes. Les systemes de facilites hierarchiques comportent plusieurs niveaux de facilites de service chacun fournissant des services differents mais relies. Le systeme specifique hierarachique de localisation, qui est modelise dans cet article, prend la forme d'une hierarchie de facilites dependantes dans laquelle la localisation d'lme facilite de niveau superieur dans un site implique obligatoirement la localisation des services de tous les niveaux inferieurs dans ce site. De plus, on assume que toute demande est satisfaite directement a partir de la facilite de niveau approprie la plus pres et qu'il n'y a pas de possibilite de recours. Le probleme median d'une hierarchie dependante est formule comme un programme lineaire en variables booleennes (PLB). Le PLB resultant peut etre solutionne a l'aide de l'approche du Lagrangien avec homes duales basee sur une extension originale de la procedure de solution/7-median correspondante et sur une relaxation speciale de la formulation du PLB. Les resultats experimentaux de calcul pour des systemes de localisation a 2 niveaux et a 3 niveaux pour des reseaux de taille moderee sont presentes.

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The disruptive anti-covering location problem

European Journal of Operational Research, 2015

Dispersion is a desirable element inherent in many location problems. For example, dispersive str... more Dispersion is a desirable element inherent in many location problems. For example, dispersive strategies are used in the location of franchise stores, bank branches, defensive missile silo placement, halfway homes, and correctional facilities, or where there is need to be dispersed as much as possible in order to minimize impacts. Two classic models that capture the essence of dispersion between facilities involve: (1) locating exactly p-facilities while maximizing the smallest distance of separation between any two of them, and (2) maximizing the number of facilities that are being located subject to the condition that each facility is no closer than r-distance to its closest neighboring facility. The latter of these two problems is called the anti-covering problem, the subject of this paper. Virtually all past research has involved an attempt to solve for the “best or maximal packing” solution to a given anti-covering problem. This paper deals with what one may call the worst case solution of an anti-covering problem. That is, what is the smallest number of needed facilities and their placement such that their placement thwarts or prevents any further facility placement without violating the r-separation requirement? We call this the disruptive anti-covering location problem. It is disruptive in the sense that such a solution would efficiently prevent an optimal packing from occurring. We present an integer linear program model for this new location problem, provide example problems which indicate that very disruptive configurations exist, and discuss the generation of a range of stable levels to this problem.

Conference on Object Orientation and Navigable Databases

to evaluate the range of products currently available • to assess the total experience to date wi... more to evaluate the range of products currently available • to assess the total experience to date with object-oriented databases (OODBMS) • to compare OO and more conventional approaches with specific emphasis on distributed storage, processing, and maintenance Invitations to the workshop were issued to ten experts in the fields of OO theory, navigable databases, and object-oriented geographic information systems GIS; Caltrans personnel; NCGIA researchers; and other invited participants with knowledge and interest in the topic of the conference. The experts were Fran ois Bancilhon,

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The p-Innovation ecosystems model

arXiv (Cornell University), Aug 2, 2020

In this paper, we propose a spatially constrained clustering problem belonging to the family of 𝑝... more In this paper, we propose a spatially constrained clustering problem belonging to the family of 𝑝-regions problems. Our formulation is motivated by the recent developments of economic complexity on the evolution of the economic output through key interactions among industries within economic regions. The objective of this model consists in aggregating a set of geographic areas into a prescribed number of regions (so-called innovation ecosystems) such that the resulting regions preserve the most relevant interactions among industries. We formulate the 𝑝-Innovation Ecosystems model as a mixed-integer programming (MIP) problem and propose a heuristic solution approach. We explore a case involving the municipalities of Colombia to illustrate how such a model can be applied and used for policy and regional development.

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California Partners in Advanced Transit and Highways (PATH) Spatial and Temporal Utility Modeling

by Richard Church and Jim Marston

In the design, conduct and execution of the research we are grateful for the contribution of Prof... more In the design, conduct and execution of the research we are grateful for the contribution of Professor Mike Goodchild and the assistance of Ashleigh Day, who served as an undergraduate intern. We thank more than 2300 UCSB faculty, staff and students who participated in the travel survey and offered a variety of valuable comments.

TRANSMax II: Designing a flexible model for transit route optimization

Computers, Environment and Urban Systems, 2020

Covering path problems date from the pioneering work of Current et al. (1984, 1985). Two basic fo... more Covering path problems date from the pioneering work of Current et al. (1984, 1985). Two basic forms were defined in their work: the shortest covering path problem and the maximal covering shortest path problem. These two problems differ in that one requires complete coverage by the defined path and the other involves determining path alternatives which cover as much as possible while keeping the path length as short as possible. The latter of these two problems, the maximal covering shortest path problem, embodies the two major goals in transit planning: that is, finding efficient paths which serve as many people as possible. Often transit routes are restricted to major road segments, and when that occurs, routes do not compete with one another unless they overlap along a street segment or at an intersection. In addition, coverage distances can be quite small, barely extending to other streets. Given this type of situation, Curtin and Biba (2011) developed a model called TRANSMax (Transit Route Arc-Node Service Maximization), which maximizes node and arc service, where service coverage is defined for only those street and node segments that are part of a route. They based their model on a structure first proposed by Vajda (1961) in formulating and solving the traveling salesman problem. Because of this structure, we demonstrate that it is possible that a route generated by their original TRANSMax model may not be Pareto optimal with respect to both distance and access. In this paper, we develop a flexible TRANSMax model formulation that finds Pareto Optimal solutions when the original form does not. We also present computational experience in solving this new model on the same street network of Curtin and Biba involving Richardson, Texas. This application allows us to make comparisons between this work and the original work of Curtin and Biba. Overall, we show that this new model can identify new, improved routes over the existing TRANSMax model.

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