Abstract
We analyse how to deal with the uncertainty before solving a stochastic optimization problem and we apply it to a forestry management problem. In particular, we start from historical data to build a stochastic process for wood prices and for bounds on its demand. Then, we generate scenario trees considering different numbers of scenarios and different scenario-generation methods, and we describe a procedure to compare the solutions obtained with each approach. Finally, we show that the scenario tree used to obtain a candidate solution has a considerable impact in our decision model.
Notes
No potential conflict of interest was reported by the authors.
1 We use the words ‘demand’ and ‘sales’ as synonyms since we assume that all the production is sold.
2 From now on we refer to this as the number of unsolved samples.