Efficiency in forest management: A multiobjective harvest scheduling model

M. Hernandez, T. Gómez, J. Molina, M.A. León and R. Caballero

Journal of Forest Economics, 2014, vol. 20, issue 3, 236-251

Abstract: This paper presents a new forest harvest scheduling model taking into account four conflicting objectives. The economic factor of timber production is considered and also aspects related to environmental protection. We also incorporate adjacency constraints to limit the maximum contiguous area where clear-cutting can be applied. The model proposed is applied to a timber production plantation in Cuba located in the region of Pinar del Río. One factor to be taken into account in Cuban plantations is that the forest has a highly unbalanced age distribution. Therefore, in addition to the classical objectives of forest planning, we have the objective of rebalancing age distribution by the end of the planning horizon. Explicitly, the four objectives considered in the model are: (a) obtaining a balance-aged forest; (b) minimizing the area with trees older than the rotation age; (c) maximizing the NPV of the forest over the planning horizon; and (d) maximizing total carbon sequestration over the whole planning horizon. The solution to the proposed model provides a set of efficient management plans that are of assistance in analysing the tradeoffs between the economic and ecological objectives. The model is also applied to randomly generated simulated forests to compare its performance in other contexts. As the problem is a multiobjective binary nonlinear model, a metaheuristic procedure is used in order to solve it.

Keywords: Forest planning; Multiobjective programming; Adjacency constraints; CO2 captured; Nonlinear binary models; Metaheuristic (search for similar items in EconPapers)
JEL-codes: C02 C61 Q23 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.jfe.2014.06.002

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