Journal of System Simulation
Abstract
Abstract: The natural forest spatial structure contains the spatial location information of the forest, which affects the growth, competition and stability of the forest development. Its optimization is a multi-objective programming problem. A bee colony particle swarm optimization (ABC-PSO) hybrid algorithm is proposed, which improves the initial particle generation mechanism, the number of follow bees and the circulation mechanism. The algorithm is applied to the multi-objective optimization of the spatial structure of natural forest. An optimization model which takes account of the tree distribution grid, tree size segmentation and tree competition is established. The simulation results show that the bee colony-particle swarm optimization algorithm improves the forest health level and solves the multi-objective optimization of the forest spatial structure.
Recommended Citation
Qing, Dongsheng; Zhang, Xiaofang; Li, Jianjun; Rui, Guo; and Deng, Qiaoling
(2020)
"Spatial Structure Optimization of Natural Forest Based on Bee Colony-particle Swarm Algorithm,"
Journal of System Simulation: Vol. 32:
Iss.
3, Article 4.
DOI: 10.16182/j.issn1004731x.joss.19-0320
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol32/iss3/4
First Page
371
Revised Date
2019-09-24
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.19-0320
Last Page
381
CLC
TP391.9
Recommended Citation
Qing Dongsheng, Zhang Xiaofang, Li Jianjun, Guo Rui, Deng Qiaoling. Spatial Structure Optimization of Natural Forest Based on Bee Colony-particle Swarm Algorithm[J]. Journal of System Simulation, 2020, 32(3): 371-381.
DOI
10.16182/j.issn1004731x.joss.19-0320
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