Designing Robust Coverage Systems
A Maximal Covering Model with Geographically Varying Failure Probabilities
Bibliographic Data
| ID | 8378141 |
|---|---|
| Authors | Ting L Lei (0000-0003-2385-9128, University of California, Santa Barbara, corresponding author), Diane Tong (0000-0001-7005-5128, University of Arizona, corresponding author), Daoqin Tong, Richard L Church (0000-0003-2263-2204, University of California, Santa Barbara, corresponding author) |
| Year | 2014 |
| Volume | 104 |
| Issue | 5 |
| Pages | 922-938 |
| Publication date | 2014-09-03 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the Association of American Geographers (JOURNAL) |
| Journal identifiers | ISSN: 0004-5608 • E-ISSN: 1467-8306 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00045608.2014.923722 |
| OpenAlex | W1983012969 |
| Language | EN |
| Citations received | 2 |
| References cited | 55 |
Covering models have been used in a wide range of modeling and geospatial analysis applications ranging from planning emergency services to natural reserve design. One topic in coverage modeling that has received considerable research attention is addressing uncertainty due to facility unavailability and service disruptions. In this article, we propose a covering model that maximizes the expected coverage of demand by considering the possibility of facility failures. Unlike existing models that assume a uniform failure probability across all sites in an area, the proposed model can account for spatially varying failure probabilities and describes better the underlying geographic processes that cause facility failures. The model is posed as a spatial optimization problem using integer linear programming. We compare two different formulations of the covering model and discuss their properties. The proposed model formulations have been tested computationally using a warning sirens data set that has been widely used in assessing covering models. We conclude with a summary of findings as well as possible directions of future research
Algorithm · Cartography · Facility location problem · Geography · Geospatial analysis · Integer programming · Operations research · Range (aeronautics) · Ranging · Reliability engineering · Set (abstract data type) · Unavailability · Computer Science · Engineering · Evacuation and Crowd Dynamics · Facility Location and Emergency Management · Urban Transport and Accessibility
Central Facilities Location
Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph
The Location of Emergency Service Facilities
A lattice covering model for evaluating existing service facilities
Generalized Coverage Models and Public Facility Location
Maximising coverage of spatial demand for service
The Maximal Covering Location Problem
Generalized coverage models and public facility location
The maximal covering location problem
Geography in Coverage Modeling
Selecting sites for rural health workers
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,4 |
| Citation span | 2021 - 2023 (3) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |