Heuristics in Spatial Analysis
A Genetic Algorithm for Coverage Maximization
Datos Bibliográficos
| ID | 8374684 |
|---|---|
| Autores | Diane Tong (0000-0001-7005-5128, University of Arizona), Daoqin Tong, Alan T Murray (0000-0003-2674-6110, Arizona State University), Alan Murray (0000-0003-2621-4632), N Xiao (0000-0002-6585-6294, The Ohio State University) |
| Año | 2009 |
| Volumen | 99 |
| Número | 4 |
| Páginas | 698-711 |
| Fecha de publicación | 2009-09-17 |
| Peer Reviewed | Sí |
| Open Access | No |
| Tipo | ARTICLE |
| Revista | Annals of the Association of American Geographers (JOURNAL) |
| Identificadores de la revista | ISSN: 0004-5608 • E-ISSN: 1467-8306 |
| Editorial | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00045600903120594 |
| OpenAlex | W1989222404 |
| Idioma | EN |
| Citas recibidas | 15 |
| Referencias citadas | 40 |
Many government agencies and corporations face locational decisions, such as where to locate fire stations, postal facilities, nature reserves, computer centers, bank branches, and so on. To reach such location-related decisions, geographical information systems (GIS) are essential for providing access to spatial data and analysis tools. Moreover, geographic insights can be gained from GIS as they enable capabilities for better reflecting problems of interest in location modeling. The resulting models can be complex, however, and hence computationally challenging to solve. This article examines an important model for regional service coverage maximization. This model is solved heuristically using a genetic algorithm. The new heuristic innovatively incorporates problem-specific knowledge by exploring the geographical structure of the problem under study. Comparative application results demonstrate important nuances of the new genetic algorithm, enhancing overall performance
Business · Cartography · Data mining · Data science · Genetic algorithm · Geographic information system · Geography · Heuristic · Heuristics · Machine learning · Mathematical optimization · Maximization · Operations research · Service (business) · Spatial analysis · Utility maximization · Artificial Intelligence · Computer Science · Engineering · Facility Location and Emergency Management · Mathematics · Urban and Freight Transport Logistics · Urban Transport and Accessibility
Commentary
Spatial Optimization
Spatial Optimization Models
Optimizing the Equality of Healthcare Services in Wuhan, China, Using a New Multimodal Two-Step Floating Catchment Area Model in Conjunction with the Hierarchical Maximal Accessibility Equality Model
A heuristic algorithm for balancing workloads in coverage modeling
Identifying the spatial footprint of pollen distributions using the Geoforensic Interdiction (Gofind) model
Optimisation of surveillance camera site locations and viewing angles using a novel multi-attribute, multi-objective genetic algorithm
Exploring the Tradeoff Between Privacy and Utility of Complete‐count Census Data Using a Multiobjective Optimization Approach
Optimizing the ultra-dense 5G base stations in urban outdoor areas
Space-time demand cube for spatial-temporal coverage optimization model of shared bicycle system
Optimisation of rural roads planning based on multi-modal travel
Spatial Optimization in Geography
A Century of Method-Oriented Scholarship in the Annals
A Computational Framework for Preserving Privacy and Maintaining Utility of Geographically Aggregated Data
Geoforensics with Pollen Quantification
Adaptation in Natural and Artificial Systems
No free lunch theorems for optimization
Heuristic Methods for Estimating the Generalized Vertex Median of a Weighted Graph
Maximising coverage of spatial demand for service
The Maximal Covering Location Problem
The maximal covering location problem
Geography in Coverage Modeling
A Unified Conceptual Framework for Geographical Optimization Using Evolutionary Algorithms
Accessibility and Public Facility Location
| Obras citantes distintas | 15 |
|---|---|
| Citas por año | 0,94 |
| Intervalo de citas | 2010 - 2025 (16) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 14 |