You are here: Home
/ Publication Information
Title: A chance constraint estimation approach to optimizing resource management under uncertainty
Author: Bevers, Michael
Source: Canadian Journal of Forest Research. 37: 2270-2280.
Description: Chance-constrained optimization is an important method for managing risk arising from random variations in natural resource systems, but the probabilistic formulations often pose mathematical programming problems that cannot be solved with exact methods. A heuristic estimation method for these problems is presented that combines a formulation for order statistic observations with the sample average approximation method as a substitute for chance constraints. The estimation method was tested on two problems, a small fire organization budgeting problem for which exact solutions are known and a much larger and more difficult habitat restoration problem for which exact solutions are unknown. The method performed well on both problems, quickly finding the correct solutions to the fire budgeting problem and repeatedly finding identical solutions to the habitat restoration problem.
Keywords: resource management, chance-constrained optimization, natural resource systems, heuristic estimation method
View or Print this Publication (155 K bytes)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
Bevers, Michael 2007. A chance constraint estimation approach to optimizing resource management under uncertainty. Canadian Journal of Forest Research. 37: 2270-2280.
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility