Journal article
A parallel algorithm for coverage optimization on multi-core architectures
International journal of geographical information science : IJGIS, v 30(3), pp 432-450
03 Mar 2016
Abstract
Location siting is an important part of service provision, with much potential to impact operational efficiency, safety, security, system reliability, etc. A class of location models seeks to optimize coverage of demand for service that is continuously distributed across space. Decision-making and planning contexts include police/fire resource allocation for a community, siting cellular towers to support cell phone signal transmission, locating emergency warning sirens to alert the public of severe weather and other related dangers, and many others as well. When facilities can be sited anywhere in continuous space to provide coverage to an entire region, this is a very computationally challenging problem to solve because potential demand for service is everywhere and there are an infinite number of potential facility sites to consider. This article develops a new parallel solution approach for this location coverage optimization problem through an iterative bounding scheme on multi-core architectures. The developed approach is applied to site emergency warning sirens in Dublin, Ohio, and fire stations in Elk Grove, California. Results demonstrate the effectiveness and efficiency of the proposed approach, enabling real-time analysis and planning. This work illustrates that the integration of cyberinfrastructure can significantly improve computational efficiency in solving challenging spatial optimization problems, fitting the themes of this special issue: cyberinfrastructure, GIS, and spatial optimization.
Metrics
Details
- Title
- A parallel algorithm for coverage optimization on multi-core architectures
- Creators
- Ran Wei - University of UtahAlan T. Murray - Drexel University
- Publication Details
- International journal of geographical information science : IJGIS, v 30(3), pp 432-450
- Publisher
- Taylor & Francis
- Number of pages
- 19
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000367015800002
- Scopus ID
- 2-s2.0-84957725279
- Other Identifier
- 991019357634004721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Geography
- Geography, Physical
- Information Science & Library Science