Influência de diferentes funções objetivo em modelos de regulação florestal

Carvalho, Kaio Henrique Adame de; Silva, Márcio Lopes da; Leite, Hélio Garcia; Binoti, Daniel Henrique Breda; Silva, Liniker Fernandes da

doi:10.18227/1982-8470ragro.v10i4.3367

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…However, lower variations were observed in the Strategy 2, where the maximum volume was close to 600,000 m 3 in the first period. Similar results were obtained by Carvalho (2012), where the volume was always lower for the minimization models. According to this author, the cost minimization methods are very interesting to supply the industry demands with smaller cutting areas.…”

Section: Resultssupporting

confidence: 86%

“…This fact also indicates that the maximum production does not affect the maximum revenue. The results obtained in this research were similar to those of Carvalho (2012), where the largest production and financial return were reached by the models that maximized the forest production and net present value, respectively. The minimization models, although providing lower financial returns when compared to maximization models (Table 3), were very efficient to regulate thinning and clear-cutting, resulting in more homogeneous production over time, especially in the first years of the horizon planning.…”

Section: Resultssupporting

confidence: 81%

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Strategies for regulating timber volume in forest stands

Fiorentin¹,

Arce²,

Pelissari³

et al. 2017

Sci. For.

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ResumoOs objetivos desta pesquisa foram: 1) avaliar duas estratégias de otimização para minimizar a diferença entre a máxima e mínima produção anual e minimizar os desvios de produção entre anos consecutivos; 2) comparar a sua performance com dois modelos tradicionais para regular o fluxo de volume de madeira. O problema deste estudo representou a situação real de uma empresa localizada no estado de Santa Catarina, Brasil, onde a estrutura da floresta estava altamente irregular, devido ao predomínio de povoamentos em idades avançadas. Alternativas de manejo foram propostas para cada povoamento e a programação linear foi usada para otimizar a estrutura da floresta. As estratégias alcançaram a demanda industrial de madeira em todos os períodos do horizonte de planejamento. O modelo que maximizou a produção (Estratégia 1) e o valor presente líquido (Estratégia 2) resultou na maior produção de volume e no maior retorno financeiro, respectivamente. No entanto, produção homogêneas de madeira foram obtidas usando as funções objetivo que minimiza a oscilação entre a máxima e mínima produção anual (Estratégia 3) e o desvio da produção entre anos consecutivos (Estratégia 4), quando comparadas com modelos tradicionais (Estratégia 1 e 2). A Estratégia 4 foi a mais apropriada, pois proporcionou retorno financeiro e volume de sortimentos satisfatório a longo prazo, reduzindo possíveis problemas operacionais que podem ocorrer. Palavras-chave: AbstractThe objectives of this research were: 1) evaluating two optimization strategies for minimizing the difference between maximum and minimum annual production and minimizing the production deviation between consecutive years; 2) comparing their performance with two traditional models to regulate the flow of timber volume. The problem given in this study represented a real situation of a forest company located in the state of Santa Catarina, Brazil, where the forest structure had become highly irregular due to predominance of trees with advanced ages. We proposed management alternatives for each stand, and linear programming was used to optimize the forest structure. The strategies achieved the industrial timber demand in all periods of the planning horizon. The models that maximized the production (Strategy 1) and the net present value (Strategy 2) resulted in the highest timber volume production and the highest financial return, respectively. However, we obtained homogeneous timber production by using the objective functions that minimize the maximum and minimum annual production oscillation (Strategy 3) and deviation production between consecutive years (Strategy 4), when we compared to traditional models (Strategy 1 and 2). The Strategy 4 was the most appropriate for providing satisfactory financial return and timber volume in the long-term, reducing possible operational problems that could occur.

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Section: Resultssupporting

confidence: 86%

Section: Resultssupporting

confidence: 81%

Strategies for regulating timber volume in forest stands

Fiorentin¹,

Arce²,

Pelissari³

et al. 2017

Sci. For.

View full text Add to dashboard Cite

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“…Application of operational research tools in hierarchical forest planning can contribute meaningfully to decisionmaking (Fonseca et al, 2012;Martins et al, 2014;Hahn et al, 2014;Garcia-Gonzalo et al, 2016;Carvalho et al, 2016). However, because of the relatively large PH, there are several risks and uncertainties that this model is unable to predict (e.g.…”

Section: Resultsmentioning

confidence: 99%

Modeling the sensitivity of strategic plans to risks and uncertainties in forest management

Neto¹,

Simone²,

Santos³

et al. 2020

Afr. J. Agric. Res.

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Forest operations are associated with products of a biological source and long-term plans. This makes forest management plans affected by market and environmental uncertainties, which can cause differences between the strategic and operational plans. Risks related to disease spread, adverse weather, timber demand, and available capital can cause a reduction in planted areas. It is necessary that forest management plans aim to optimize production and reduce the effects of restrict planting. In this work, a linear programming model was created for long-term forests planning including a variable to restrict planting area. Prescriptions were defined for 6-, 7-and 8-year rotation considering planting or coppicing, creating 60 scenarios varying intensity, period and time of reductions in the planted areas. All scenarios were evaluated by the NPV at the end of the planning horizon. The results showed that the NPV decreased when the planted area was reduced and when the reductions took place at the beginning of the planning horizon. The differences were between 24.1 and 0.07% in relation to the conventional scenario (no planting restriction). The differences were not higher because prescriptions changed from planting to coppice.

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“…Forest management is the application of analytical techniques in the selection of management alternatives to meet the objectives of a company or forestry organisation (Bettinger et al, 2017;Araujo et al, 2018). The best choice among these alternatives depends on the accuracy of information on forest resources (both data and models used to estimate and predict population variables, like wood volume), (Carvalho et al, 2016) and the intensity of interventions during the planning horizon (Clutter et al, 1983;Duvemo and Lämas, 2006). Due to the substantial investments required for management of timber production, highly accurate models of tree attributes and stand development are required (Burkhart and Tomé, 2012).…”

Section: Introductionmentioning

confidence: 99%

Effect of growth and yield modelling on forest regulation and earnings

Vescovi¹,

Leite²,

Soares³

et al. 2020

Afr. J. Agric. Res.

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The elaboration of a forest schedule involves constructing and solving a forest regulation model. The regulated structure is not easy to obtain, considering the fluctuations in the effective planting area during the planning horizon, technological advances, and changes in annual demand. Nevertheless, the establishment and implementation of a regulation model often results in an improvement of the forest, in terms of the distribution of age classes. The successful use of regulation models and consequent definition of a forest management plan depends on the quality of data from forest inventory plots and prediction accuracy of stand wood stock. This study evaluated the effect of different alternatives of growth and yield modelling on the regulation of a eucalyptus even-aged forest. Each alternative was used to create yield tables, which were used as inputs in a linear programming model. In this model, restrictions of area, demand, and regulation were included, with the goal of maximising the total net present value. The most consistent forest schedule was obtained with a total stand model.

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Influência de diferentes funções objetivo em modelos de regulação florestal

Cited by 3 publications

References 13 publications

Strategies for regulating timber volume in forest stands

Strategies for regulating timber volume in forest stands

Modeling the sensitivity of strategic plans to risks and uncertainties in forest management

Effect of growth and yield modelling on forest regulation and earnings

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