Optimizing forest road planning in a sustainable forest management area in the Brazilian Amazon.

Marcelo Otone Aguiar,Gilson Fernandes da Silva, Geraldo Regis Mauri,Adriano Ribeiro de Mendonça, Cesar Junio de Oliveira Santana,Gustavo Eduardo Marcatti, Mayra Luiza Marques da Silva,Evandro Ferreira da Silva, Evandro Orfano Figueiredo,Jeferson Pereira Martins Silva, Rodrigo Freitas Silva,Jeangelis Silva Santos, Gabriel Lessa Lavagnoli,Catherine Cristina Claros Leite

Journal of environmental management(2021)

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摘要
The construction of forest roads in Brazilian Amazon is costly and has a significant environmental impact. Several practices and principles must be observed to comply with legislation, to preserve the remaining forest, and to ensure sustainable exploitation. Road planning is complex in this context, based on the number of aspects and variables that must be considered. This research aimed to evaluate computational methods' effectiveness in planning forest roads, optimizing resources to reduce damage to the remaining forest, compared to traditional planning methods. The study area was a native forest under a sustainable forest management regime located in municipalities of Terra Santa and Oriximiná, in Pará, in Brazilian Amazon. Data obtained from area made it possible formulate six instances of different sizes. A binary integer linear programming model was used, solved using CPLEX software, and Dijkstra, Bellman-Ford, Dial, and D'Esopo-Pape shortest path algorithm, implemented in C programming language. During processing of instances, the time taken to obtain the solution increased according to size of instance, however, time difference was not significant. Among the evaluated algorithms, the D'Esopo-Pape algorithm showed the best performance. The evaluated methods were effective in obtaining an optimal solution for proposed forest road planning. The solutions obtained using computational methods more effectively considered the restrictions associated with sustainable forest management, in contrast to those derived from the traditional planning by forestry company.
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