Agendamento otimizado da colheita de madeira de eucaliptos sob restrições operacionais, espaciais e climáticas
Bibliographic record
Abstract
The representation of sustainability concerns in industrial forests management plans, in relation to environmental, social and economic aspects, involve a great amount of details when analyzing and understanding the interaction among these aspects to reduce possible future impacts. At the tactical and operational planning levels, methods based on generic assumptions usually provide non-realistic solutions, impairing the decision making process. This study is aimed at improving current operational harvesting planning techniques, through the development of a mixed integer goal programming model. This allows the evaluation of different scenarios, subject to environmental and supply constraints, increase of operational capacity, and the spatial consequences of dispatching harvest crews to certain distances over the evaluation period. As 1Mestre em Recursos Florestais pelo Departamento de Ciencias Florestais da Escola Superior de Agricultura “Luiz de Queiroz” da Universidade de Sao Paulo Av. Padua Dias, 11 Piracicaba, SP 13418-900 – E-mail: jbanhara@gmail.com 2Professor Associado do Departamento de Ciencias Florestais da Escola Superior de Agricultura “Luiz de Queiroz” da Universidade de Sao Paulo Av. Padua Dias, 11 Piracicaba, SP 13418-900 – E-mail: luiz.estraviz@esalq.usp.br; fseixas@esalq.usp.br 3Pesquisador da Empresa Brasileira de Pesquisa Agropecuaria (Embrapa Cerrados) SQN 405 Bloco I Apto 307 Asa Norte – Brasilia, DF 70846-090 – E-mail: jose.moreira@cpac.embrapa.br 4Mestre em Recursos Florestais Gerente Regional de Operacoes Florestais da Savcor Forest Av. Joao Guilhermino, 261 Sao Jose dos Campos, SP 12210-131 – E-mail: lana.silva@savcor.com 5Mestre em Recursos Florestais Diretora de Solucoes da Savcor Forest Av. Joao Guilhermino, 261 Sao Jose dos Campos, SP 12210-131 – E-mail: silvana.nobre@savcor.com 6Diretor de Treinamentos da Remsoft 160-77 Westmorland St. Fredericton, New Brunswick, Canada E3B 6Z3 – E-mail: andrew@remsoft.com Banhara et al. Agendamento otimizado da colheita de madeira de eucaliptos sob restricoes operacionais, espaciais e climaticas 86 Sci. For., Piracicaba, v. 38, n. 85, p. 85-95, mar. 2010 a result, a set of performance indicators was selected to evaluate all optimal solutions provided to different possible scenarios and combinations of these scenarios, and to compare these outcomes with the real results observed by the mill in the study case area. Results showed that it is possible to elaborate a linear programming model that adequately represents harvesting limitations, production aspects and environmental and supply constraints. The comparison involving the evaluated scenarios and the real observed results showed the advantage of using more holistic approaches and that it is possible to improve the quality of the planning recommendations using linear programming techniques.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".