Comparison of population-based algorithms for optimizing thinnings and rotation using a process-based growth model

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http://hdl.handle.net/10138/310435

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Xue , H , Mäkelä , A A , Valsta , L T , Vanclay , J & Cao , T 2019 , ' Comparison of population-based algorithms for optimizing thinnings and rotation using a process-based growth model ' , Scandinavian Journal of Forest Research , vol. 34 , no. 6 , pp. 458-468 . https://doi.org/10.1080/02827581.2019.1581252

Title: Comparison of population-based algorithms for optimizing thinnings and rotation using a process-based growth model
Author: Xue, Hailian; Mäkelä, Aino Annikki; Valsta, Lauri Tapani; Vanclay, Jerome; Cao, Tianjian
Contributor: University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
Date: 2019-08-18
Language: eng
Number of pages: 11
Belongs to series: Scandinavian Journal of Forest Research
ISSN: 0282-7581
URI: http://hdl.handle.net/10138/310435
Abstract: Stand management optimization has long been computationally demanding as increasingly detailed growth and yield models have been developed. Process-based growth models are useful tools for predicting forest dynamics. However, the difficulty of classic optimization algorithms limited its applications in forest planning. This study assessed alternative approaches to optimizing thinning regimes and rotation length using a process-based growth model. We considered (1) population-based algorithms proposed for stand management optimization, including differential evolution (DE), particle swarm optimization (PSO), evolution strategy (ES), and (2) derivative-free search algorithms, including the Nelder–Mead method (NM) and Osyczka’s direct and random search algorithm (DRS). We incorporated population-based algorithms into the simulation-optimization system OptiFor in which the process-based model PipeQual was the simulator. The results showed that DE was the most reliable algorithm among those tested. Meanwhile, DRS was also an effective algorithm for sparse stands with fewer decision variables. PSO resulted in some higher objective function values, however, the computational time of PSO was the longest. In general, of the population-based algorithms, DE is superior to the competing ones. The effectiveness of DE for stand management optimization is promising and manifested.
Subject: 4112 Forestry
Algorithm performance
optimal thinning
population-based algorithms
process-based model
CARBON-BALANCE
STAND MANAGEMENT
SIMPLEX-METHOD
OPTIMIZATION
PRODUCTIVITY
SEARCH
PINE
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