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Title: Planejamento operacional da colheita sob condições de incerteza na manutenção de estradas
Other Titles: Operational harvest planning under uncertainty conditions in road maintenance
Authors: Gomide, Lucas Rezende
Silva, Carolina Souza Jarochinski e
Gomide, Lucas Rezende
Silva, Carolina Souza Jarochinski e
Santana, Cesar Junio de Oliveira
Keywords: Planejamento florestal
Processo estocástico
Programação linear
Método de Monte Carlo
Forestry planning
Stochastic process
Linear programming
Monte Carlo method
Issue Date: 26-May-2021
Publisher: Universidade Federal de Lavras
Citation: GOMES, V. de S. Planejamento operacional da colheita sob condições de incerteza na manutenção de estradas. 2021. 76 p. Dissertação (Mestrado em Engenharia Florestal) – Universidade Federal de Lavras, Lavras, 2021.
Abstract: Forest planning plays an important role in managing production chain activities. Such planning uses operational research (OR) tools to assist in the decision-making process. Mathematical models of stochastic nature can represent real problems and find viable solutions to planning problems. Also, the uncertainty approach can better direct the forest operations planning faced with unexpected events, allowing anticipation of possible expenditures during execution. In this context, this work approaches the problem of operational planning of the harvest under uncertainty of forest road maintenance. Thus, we structured the dissertation into two parts. The first consists of a bibliographical survey of the state of the art on the planning of the forest road network and optimization methods used in problem solving. In the second part, we conducted a case study. We propose an Integer Linear Programming (ILP) model of a stochastic nature to analyze the effects of forest roads maintenance delays on the scheduling of the forest harvest. Our results show that the random effects of the forest road maintenance delays provide great variability in the value of objective functions. The timber volume harvested over the planning horizon varies considerably with periods which the value is zero. Therefore, the stochastic model proposed can be useful to assist managers in decision making. In addition, the approach also may help the road classification and reducing risks for better management practices.
Appears in Collections:Engenharia Florestal - Mestrado (Dissertações)

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