Decision Making on Sustainable Forest Harvest Production Using Goal Programming Approach (Case Study: Iranian Hyrcanian Forest)

Abstract

This paper aims to determine the optimal stock level in Hyrcanian forest of Iran. In this study, a goal programming techniques used to estimate the optimum stock level of different tree species considering economics, environmental and social issues. We consider multiple objectives in the process of decision making to realize the balance of maximizing annual growth, net present value, carbon sequestration and labor. We use regression analysis to develop a forest growth model using allometric functions for the quantification of carbon budget. The expected mean price was estimated to determine the net present value of forest harvesting. We use Expert knowledge to weight the goals in order to generate the optimal stock level. Results show that the total optimum stock is 0.5%lower than based on questioners. The results indicate that goal programming is a suitable methodology in this case.