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Pragmatic Approaches to Optimization with Random Yield Coefficients

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This paper discusses practical methods for handling normally distributed random technical (yield) coefficients in linear programs that optimize natural resource allocation and scheduling. These methods are practical in the sense that they are applicable to large-scale real world models and do not require nonlinear solution methods. The paper begins with a description and demonstration of postoptimization approaches that are applicable to large, linear problems, and then explores methods for reducing overall risk through land allocation diversification. A central theme of the paper is the importance of providing some sort of allowance for uncertainty when presenting optimization results, which promotes a more realistic view of the problem by analysts and decision makers alike. For. Sci. 41(3):501-512.

Keywords: Linear programming; chance constraints; probabilistic programming

Document Type: Journal Article

Affiliations: Professor, Michigan Technological University, Houghton, MI

Publication date: August 1, 1995

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    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
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