Covering Problem Applied for Allocation of Storage Yards in Sustainable Forest Management (SFM)
Year: 2025
Type: conference-paper
Abstract: Context: Providing resources for a growing population is a challenge. Sustainable forest management emerges as an alternative for resource extraction from native forests in a planned manner, ensuring balance in the activity. Problem: Although SFM brings benefits, companies often plan their logging operations empirically, failing to achieve the best balance between resource efficiency and forest preservation. The optimal location of wood storage yards influences the construction of roads and skid trails, offering both economic and environmental benefits by minimizing the hauling distance for timber. Solution: An adaptation of the covering problem is proposed to create an optimization model for the allocation of wood storage yards within the scope of SFM. IS Theory: The forest ecosystem can be seen as a complex system, where ecological, social, and economic variables are considered to sustainably optimize resources. Method: To evaluate the effectiveness of optimizing yard allocation, a quantitative study was conducted using a computational model applied to a dataset provided by Aguiar et al. (2020).A comparative analysis approach was used to compare the model’s results with the data from the aforementioned study. Summary of Results: The results demonstrate that the model was effective in determining optimal locations for the yards. Compared to the p-median problem, it offers the additional benefit of eliminating the need to specify the number of yards, allowing for generalization to other datasets. Contributions and Impact on IS: This work shows how intelligent systems can optimize complex processes, promoting sustainable natural resource management and technological innovation in the forestry sector. It serves as a foundation for future studies in optimization and environmental management.
Authors: Dalvan Ribeiro de Almeida, Marcelo Otone Aguiar, Danilo de Paula e Silva
Language: English
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4410159347