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. Copyright (c) 2008, Wiley Periodicals, Inc.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.