Optimal forest management decision making using goal programming and fuzzy analytic hierarchy process approaches in Hyrcanian mixed forests

The aim of this research is to determine the optimal stock level in Hyrcanian forest of Iran. In this study, a goal programming techniques was used in order to estimate the optimal stock level of different tree species considering economics, environmental and social issues. Multiple objectives in the process of decision making were considered to maximize the net present value, carbon sequestration and labor. Regression analysis was used to develop a forest growth model. In addition, an allometric function was used to determine the amount of carbon sequestration. Expected mean price is estimated using wood price and variable harvesting costs to determine the net present value of forest harvesting. The fuzzy analytic hierarchy process is applied to determine the weights of goals using questionnaires filled by experts in order to determine the optimal stock level. Results showed that the optimal volumes were 256.2 m3⋅ha-1, 61.2 m3⋅ha-1, 38.8 m3⋅ha-1, 20.4 m3⋅ha-1 for, and 20.4 m3⋅ha-1 for beech, hornbeam, oak, alder and the other species, respectively. Furthermore, the results indicated that the total optimal volume is 397.005 m3⋅ha-1.