Optimising Forest Management Using Multi-Objective Genetic Algorithms

Isabel Castro, Raúl Salas-González, Beatriz Fidalgo (), José Torres Farinha and Mateus Mendes ()
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Isabel Castro: Coimbra Institute of Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal
Raúl Salas-González: RCM2+, Polytechnic University of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal
Beatriz Fidalgo: Coimbra Agriculture School, Polytechnic University of Coimbra, Bencanta, 3045-601 Coimbra, Portugal
José Torres Farinha: Coimbra Institute of Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal
Mateus Mendes: Coimbra Institute of Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes, 3030-199 Coimbra, Portugal

Sustainability, 2024, vol. 16, issue 23, 1-23

Abstract: Forest management requires balancing ecological, economic, and social objectives, often involving complex optimisation problems. Traditional mathematical methods struggle with these challenges, leading to the adoption of metaheuristic approaches like the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). This paper introduces a custom NSGA-II algorithm, incorporating a specialised mutation operator to enhance solution generation for multi-objective forest planning. The custom NSGA-II is compared to the standard NSGA-II in a scenario aiming to maximise timber harvest volume and minimise its standard deviation, with a minimum volume constraint. Key performance metrics include non-dominated solutions, spacing, computational cost, and hypervolume. The results demonstrate that the custom NSGA-II provides more valid solutions and better explores the solution space. This approach offers a user-friendly and efficient tool for forest managers, integrating well with Web-based systems for modern, sustainability-oriented forest planning.

Keywords: forest management; optimization; Genetic Algorithm; multi-objective optimization; sustainability; Web integration (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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