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Strategies for Solving Large Location-Allocation Problems by Heuristic Methods

Bibliographic Data

ID4922730
AuthorsP J Densham (National Center for Geographic Information and Analysis, and Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA), G Rushton (San Diego State University)
Year1992
Volume24
Issue2
Pages289-304
Publication date1992-02-01
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning A Economy and Space (JOURNAL)
Journal identifiersISSN: 0308-518X • E-ISSN: 1472-3409
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1068/a240289
OpenAlexW2079970366
LanguageEN
Citations received12
References cited14

Solution techniques for location-allocation problems usually are not a part of microcomputer-based geoprocessing systems because of the large volumes of data to process and store and the complexity of algorithms. In this paper, it is shown that processing costs for the most accurate, heuristic, location-allocation algorithm can be drastically reduced by exploiting the spatial structure of location-allocation problems. The strategies used, preprocessing interpoint distance data as both candidate and demand strings, and use of them to update an allocation table, allow the solution of large problems (3000 nodes) in a microcomputer-based, interactive decisionmaking environment. Moreover, these strategies yield solution times which increase approximately linearly with problem size. Tests on four network problems validate these claims

Computer network · Data mining · Geoprocessing · Heuristic · Location-allocation · Mathematical optimization · Microcomputer · Preprocessor · Resource allocation · Computer Science · Facility Location and Emergency Management · Mathematics · Urban and Freight Transport Logistics · Vehicle Routing Optimization Methods · Artificial Intelligence

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    Open Access•Joel D Barkan, Paul J Densham et al.•American Journal of Political…•2006

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Citations per year0.35
Citation span1992 - 2012 (21)
Highly citedNo

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