An Integer Optimization Approach to a Probabilistic Reserve Site Selection Problem

Robert G. Haight (), Charles S. Revelle () and Stephanie A. Snyder ()
Additional contact information
Robert G. Haight: U.S.D.A. Forest Service, North Central Research Station, 1992 Folwell Avenue, St. Paul, Minnesota 55108
Charles S. Revelle: Johns Hopkins University, Department of Geography and Environmental Engineering, 313 Ames Hall, Baltimore, Maryland 21218
Stephanie A. Snyder: Minnesota Department of Transportation, 108 Cecil Street SE, Minneapolis, MN 55919

Operations Research, 2000, vol. 48, issue 5, 697-708

Abstract: Interest in protecting natural areas is increasing as development pressures and conflicting land uses threaten and fragment ecosystems. A variety of quantitative approaches have been developed to help managers select sites for biodiversity protection. The problem is often formulated to select the set of reserve sites that maximizes the number of species or ecological communities that are represented, subject to an upper bound on the number or area of selected sites. Most formulations assume that information about the presence or absence of species in the candidate sites is known with certainty. Because complete information typically is lacking, we developed a reserve selection formulation that incorporates probabilistic presence-absence data. The formulation was a discrete 0/1 optimization model that maximized the number of represented vegetation communities subject to a budget constraint, where a community was considered represented if its probability of occurrence in the set of selected sites exceeded a specified minimum reliability threshold. Although the formulation was nonlinear, a log transformation allowed us to represent the problem in a linear format that could be solved using exact optimization methods. The formulation was tested using a moderately sized reserve selection problem based on data from the Superior National Forest in Minnesota.

Keywords: Environment: protected natural reserves on national forests; Programming; integer: discrete 0/1 by exact solution methods; Probability; applications: presence-absence data of species in reserves (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (35)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.48.5.697.12411 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:48:y:2000:i:5:p:697-708

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().