Adaptive optimization of forest management in a stochastic world

Abstract

Management decisions should be based on the sequentially revealed information concerning prices, growth, physical damages etc. Future flexibility is valuable in a stochastic world and should be optimized. Stochastic dynamic programming, stochastic scenario tree optimization, and optimization of adaptive control functions with stochastic simulation of the objective function are relevant alternatives.