Stochastic goal programming in forest planning

Abstract

Developing a forest management plan in a multicriteria perspective is traditionally accomplished utilizing simulation and optimization tools as a means to predict and optimize a variety of criteria under consideration. Goal programming is a useful tool to balance conflicting aspects of the competing criteria. When information regarding an aspect of uncertainty is available, stochastic programming should be utilized to efficiently integrate this additional information. Research has been conducted into determining the accuracy of forest inventory methods; however, the measurement error is typically ignored when generating forest management plans. Through integrating the uncertainty in a systematic fashion, the forest management plan can be improved by describing the potential uncertainty in the plan and by managing the influences of this uncertainty. This paper develops three stochastic goal programming formulations and highlights the usefulness of the approach on a small forest holding.