@article {Hof:1991-03-01T00:00:00:0015-749X:308,
author = "Hof, John G. and Pickens, James B.",
title = "Chance-Constrained and Chance-Maximizing Mathematical Programs in Renewable Resource Management",
journal = "Forest Science",
volume = "37",
number = "1",
year = "1991-03-01T00:00:00",
abstract = "This paper discusses a broad range of approaches to optimizing natural resource allocation in the situation where amounts of available input(s) and/or amounts of desired output(s) are random. The paper begins by reviewing, the classic approach to this class of problems, "chance-constrained programming," followed by a discussion of "joint probability chance-constrained programming," and a new alternative "total probability chance-constrained programming." The paper then develops three "chance-maximizing" counterparts. Specific formulations for executing these approaches in natural resource management problems are developed that explicitly include the cumulative probability density functions. A forestry case example demonstrates .solution procedures and shows that the different approaches can yield substantially different results. Results from different solution procedures are also compared. For. Sci. 37(1):308-325.",
pages = "308-325",
url = "http://www.ingentaconnect.com/content/saf/fs/1991/00000037/00000001/art00023",
keyword = "nonlinear programming, random right-hand sides, risk and uncertainty, stochastic models, Linear programming"
}