Estimating the value of wood quality information in constrained optimization
Abstract:In recent years, forest information has been evaluated increasingly through its value in decision making, not solely through its statistical accuracy. The value of forest information is rooted in the ability to make better decisions with better data. When the adopted option differs from the optimal, it incurs suboptimality losses, defined as the difference between the outcome (typically NPV) of the optimal and selected options. In this study, we analyse the value of timber quality information for the timber buyer selecting stands to be purchased with a given budget or demand constraint. In the basic constrained linear programming approach, the option selected as optimal with erroneous data may prove to be infeasible when evaluated with error-free data. To properly estimate the value of information, the costs of violating the constraints need to be included. We present a stochastic goal programming approach for solving this problem in which the violations are penalized with the interest of a loan, in the case of budget constraint, and with diminishing revenues, in the case of demand constraints. We show that information on timber quality has value to the buyer, increasing with the penalty. The value varied from 0 to about 80 €·ha–1, assuming only the timber quality assessments to be uncertain. Using the stochastic solution instead of expected value solution also has value for the buyer.
Document Type: Research Article
Affiliations: 1: University of Helsinki, Department of Forest Sciences, Helsinki, Finland FIN-00014. 2: Finnish Forest Research Institute, Vantaa, Finland FIN-01301. 3: Finnish Forest Research Institute, Suonenjoki, Finland FIN-77600.
Publication date: July 1, 2012
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