Forest management decision-making using goal programming and fuzzy analytic hierarchy process approaches (case study: Hyrcanian forests of Iran)

https://doi.org/10.17221/46/2019-JFSCitation:Etemad S.S., Mohammadi Limaei S., Olsson L., Yousefpour R. (2019): Forest management decision-making using goal programming and fuzzy analytic hierarchy process approaches (case study: Hyrcanian forests of Iran). J. For. Sci., 65: 368-379.
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The aim of this study is to determine the optimum stock level in the forest. In this research, a goal programming method was used to estimate the optimal stock level of different tree species considering environmental, economic and social issues. We consider multiple objectives in the process of decision-making to maximize carbon sequestration, net present value and labour. We used regression analysis to make a forest growth model and allometric functions for the quantification of carbon budget. 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 in by experts in order to generate the optimal stock level. According to the results of integrated goal programming approach and fuzzy analytic hierarchy processes, optimal volume for each species was calculated. The findings indicate that environmental, economic and social outcomes can be achieved in a multi-objective forestry program for the future forest management plans.

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