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

Seyedeh Soma Etemad, Soleiman Mohammadi Limaei (), Leif Olsson and Rasoul Yousefpour
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Seyedeh Soma Etemad: Department of Forestry, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran
Leif Olsson: Department of Information Systems and Technology, Faculty of Sciences, Technology and Media, Mid Sweden University, Sundsvall, Sweden
Rasoul Yousefpour: Department of Forestry Economics and Forest Planning, University of Freiburg, Freiburg, Germany

Journal of Forest Science, 2019, vol. 65, issue 9, 368-379

Abstract: 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.

Keywords: multipurpose forest management; fuzzy AHP; harvest scheduling; carbon sequestration (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:65:y:2019:i:9:id:46-2019-jfs

DOI: 10.17221/46/2019-JFS

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