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ENHANCING SPATIAL REPRESENTATION IN PRIMARY AND SECONDARY COVERAGE LOCATION MODELING *
Author(s) -
Kim Kamyoung,
Murray Alan T.
Publication year - 2008
Publication title -
journal of regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.171
H-Index - 79
eISSN - 1467-9787
pISSN - 0022-4146
DOI - 10.1111/j.1467-9787.2008.00575.x
Subject(s) - backup , computer science , representation (politics) , abstraction , service (business) , operations research , mathematics , database , politics , political science , law , philosophy , economy , epistemology , economics
An important goal in many planning contexts is maximizing primary and secondary (or backup) coverage while locating a specified number of service facilities. In general, we are interested in providing the greatest level of coverage to demand that is continuously distributed across space. A critical issue is how to represent continuous demand in coverage analysis, reducing or eliminating error and uncertainty. This paper evaluates representation issues in primary and secondary coverage location modeling. To overcome representational limitations, enhancements for spatial coverage abstraction are introduced and incorporated in a mathematical optimization model. In addition to model improvements, this paper introduces a new and novel error assessment approach arising due to the existence of multiple objectives. Surveillance sensor siting in an urban area is utilized to assess enhanced modeling capabilities.