Enhancing Classic Coverage Location Models

Abstract

An important area of regional science has long been location analysis and modeling. Its significance continues, now more formally known as location science, and has evolved because of the need to address complex facility siting problems and issues. This article focuses on classic coverage location problems, and how advances along theoretical and methodological fronts have enabled such problems to be viewed in new ways. Specifically, notions of implicit and explicit coverage, along with geographic information systems (GIS), provide the capacity to reconceptualize as well as better model intended planning goals and objectives. This article reviews covering problems and presents a comparative framework for both linkage and assessment. This research is significant because evolving models enable issues of frame independence, and the modifiable area unit problem, to be addressed, making planning and analysis more reliable and valuable.

Optimizing green space locations to reduce daytime and nighttime urban heat island effects in Phoenix, Arizona

“…The approach taken extends the coverage location model of Church and ReVelle (1974) (see also Church & Murray 2009;Murray, Tong, & Kim, 2010) in a number of ways. Specially, the nature of benefits differs, where β i accounts for direct cooling benefits.…”

Anti-covering Problems

“…where, for each i D 1; : : : ; p, B i .x i / gives the set of points covered by facility i; i.e., the disc centered at x i and radius R i : Hence, the problem is reduced to calculating areas of intersections of discs B i .x i / with the subregions A j : Such calculation, although cumbersome in general, are supported in GIS, see Kim and Murray (2008), Murray et al (2009), Tong and. Needless to say, the density f does not need to be piecewise constant, and one can take, for instance, a mixture of bivariate gaussians, f .a/ D P r j D1 !…”

A Hierarchical Approach to Optimizing Bus Stop Distribution in Large and Fast Developing Cities

“…In addition to the LSCP model, Murray et al [12] have summarized another two basic types of deterministic coverage location models: the model of maximal covering location problem (MCLP) that allows covering as much demand as possible using a limited number of facilities, and those that increase the likelihood of facility availability through the provision of backup coverage by lower-level facilities. There is also multi-level location set covering problem (ML-LSCP), in which facilities need to cover demand points a number of times while demand is also changing [13].…”