Evaluating the required scenario set size for stochastic programming in forest management planning: incorporating inventory and growth model uncertainty

Developing a plan of action for the future use of forest resources requires a way to predict the development of the forest through time. These predictions require the use of inventory data and growth models which contain a large number of uncertainties. These uncertainties impact the quality of the predictions and if the uncertainties are not accounted for, can lead to the selection of a suboptimal management plan. To account for and manage the uncertainties and the associated risk we have explored the use of stochastic programming. Stochastic programming can integrate uncertainty into the optimization process by solving the problem for a large number of potential scenarios of the forests future development. The selection of an appropriately sized set of scenarios involves a trade-off between tractability issues and problem representation issues. In this paper an analysis of the trade-offs is conducted. Two cases are studied, one where only the uncertainty of the inventory data is included, and a second where both growth model and inventory data uncertainty are included. The impact on increasing the number of scenarios to the problem representation is examined through a simple even-flow problem.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author