Spatial Structure Optimization of Natural Forest Based on Bee Colony-particle Swarm Algorithm

doi:10.16182/j.issn1004731x.joss.19-0320

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.

Key words: natural forest spatial structure, artificial bee colony algorithm, particle swarm algorithm, ABC-PSO algorithm, multi- objective optimization model

CLC Number:

TP391.9

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.

References

[1] 王懿祥, 陈永刚, 汤孟平, 等. 基于GIS和.NET的插件式森林空间结构分析系统[J]. 浙江农林大学学报, 2011, 28(5): 720-726.
Wang Yixiang, Chen Yonggang, Tang Mengping, et al.A plugin analysis system for forest spatial structure based on GIS and.NET[J]. Journal of Zhejiang A & F University, 2011, 28(5): 720-726.
[2] 汤孟平. 森林空间结构研究现状与发展趋势[J]. 林业科学, 2010, 46(1): 117-122.
Tang Mengping.Advances in Study of Forest Spatial Structure[J]. Scientia Silvae Sinicae, 2010, 46(1): 117-122.
[3] 卿东升. 基于蜂群-粒子群算法的森林空间结构多目标优化研究[D]. 长沙: 中南林业科技大学, 2018.
Qing Dongsheng.Multi-objective optimization of forest spatial structure based on bee colony-particle swarm algorithm [D]. Changsha: Central South University of Forestry and Technology, 2018.
[4] Mazziotta A, Podkopaev D, Triviño M, et al.Quantifying and resolving conservation conflicts in forest landscapes via multiobjective optimization[J]. Silva Fennica (S2242-4075), 2017, 51(1): 1-19.
[5] Triviño M, Pohjanmies T, Mazziotta A, et al.Optimizing management to enhance multifunctionality in a boreal forest landscape[J]. Journal of Applied Ecology (S0021-8901), 2017, 54(1): 61-70.
[6] Qin H, Dong L, Huang Y J F. Evaluating the Effects of Carbon Prices on Trade-Offs between Carbon and Timber Management Objectives in Forest Spatial Harvest Scheduling Problems: A Case Study from Northeast China[J]. Forests (S1999-4907), 2017, 8(2): 43.
[7] 王建明, 吴保国, 梁其洋. 基于遗传算法的森林抚育间伐小班智能选择[J]. 林业科学, 2017, 53(9): 63-72.
Wang Jianming, Wu Baoguo, Liang Qiyang.Forest Thinning Subcompartment Intelligent Selection Based on Genetic Algorithm[J]. Scientia Silvae Sinicae, 2017, 53(9): 63-72.
[8] 吕勇, 臧颢, 万献军, 等. 基于林层指数的青椆混交林林层结构研究[J]. 林业资源管理, 2012 (3): 81-84.
Lü Yong, Zang Hao, Wan Xianjun, et al.Storey Structure Study of Cyclobalanopsis myrsinaefolia Mixed Stand Based on Storey Index[J]. Forest Resources Management, 2012 (3): 81-84.
[9] 胡艳波, 惠刚盈. 一种新的基于混交度的林木种群分布格局测度方法[J]. 北京林业大学学报, 2015, 37(1): 9-14.
Hu Yanbo, Hui Gangying.A new method for measuring population distribution patterns of forest trees based on the mingling degree[J]. Journal of Beijing Forestry University, 2015, 37(1): 9-14.
[10] 惠刚盈, Gadow K V, Matthias Albert.一个新的林分空间结构参数—大小比数[J]. 林业科学研究, 1999, 12(1): 1-6.
Hui Gangying, Gadow K V, Matthias Albert.A new stand spatial structure parameter --size ratio[J]. Forest Research, 1999, 12(1): 1-6.
[11] 李建军, 李际平, 刘素青, 等. 基于Hegyi改进模型的红树林空间结构竞争分析[J]. 中南林业科技大学学报, 2010, 30(12): 23-27.
Li Jianjun, Li Jiping, Liu Suqing, et al.The Mangrove spatial structure competitive analysis based on Hegyi improved model[J]. Journal of Central South University of Forestry and Technology, 2010, 30(12): 23-27.
[12] 惠刚盈, Gadow K V, 胡艳波. 林分空间结构参数角尺度的标准角选择[J]. 林业科学研究, 2004, 17(6): 687-692.
Hui Gangying, Gadow K V, Hu Yanbo.The Optimum Standard Angle of the Uniform Angle Index[J]. Forest Research, 2004, 17(6): 687-692.
[13] 胡艳波, 惠刚盈. 基于相邻木关系的林木密集程度表达方式研究[J]. 北京林业大学学报, 2015, 37(9): 1-8.
Hu Yanbo, Hui Gangying.How to describe the crowding degree of trees based on the relationship of neighboring trees[J]. Journal of Beijing Forestry University, 2015, 37(9): 1-8.
[14] 胡艳波. 基于结构化森林经营的天然异龄林空间优化经营模型研究[D]. 北京: 中国林业科学研究院, 2010.
Hu Yanbo.Structure-based Spatial Otimization Management Modle for Natural Uneven-aged Forest[D]. Beijing: Chinese Academy of Forestry, 2010.
[15] 李建军, 张会儒, 刘帅, 等. 基于改进PSO的洞庭湖水源涵养林空间优化模型[J]. 生态学报, 2013, 33(13): 4031-4040.
Li Jianjun, Zhang Huiru, Liu Shuai, et al.A space optimization model of water resource conservation forest in Dongting
Lake based on improved PSO[J]. Acta Ecologica Sinica, 2013, 33(13): 4031-4040.
[16] 张江. 森林健康经营空间途径与评价系统研究[D]. 长沙: 中南林业科技大学, 2014.
Zhang Jiang.The study of Space Approaches and Evaluation System on the forest healthy management [D]. Changsha: Central South University of Forestry Science and Technology, 2014.
[17] 刘帅. 天然次生林林分结构分析及多目标智能优化研究[D]. 长沙: 中南林业科技大学, 2017.
Liu Shuai.Structural analysis and multi-objective intelligent optimization of natural secondary forests[D]. Changsha: Central South University of Forestry Science and Technology, 2017.
[18] 陈美蓉, 郭一楠, 巩敦卫, 等. 一类新型动态多目标鲁棒进化优化方法[J]. 自动化学报, 2017, 43(11): 2014-2032.
Chen Meirong, Guo Yinan, Gong Dunwei, et al.A Novel Dynamic Multi-objective Robust Evolutionary Optimization Method[J]. Acta Automatica Sinica, 2017, 43(11): 2014-2032.
[19] 丁进良, 杨翠娥, 陈立鹏, 等. 基于参考点预测的动态多目标优化算法[J]. 自动化学报, 2017, 43(2): 313-320.
Ding Jinliang, Yang Cuie, Chen Lipeng, et al.Dynamic Multi-objective Optimization Algorithm Based on Reference Point Prediction[J]. Acta Automatica Sinica, 2017, 43(2): 313-320.
[20] 郑丽凤, 周新年, 胡喜生, 等. 择伐作业体系下天然林直径分布[J]. 东北林业大学学报, 2009, 37(9): 22-24.
Zheng Lifeng, Zhou Xinnian, Hu Xisheng, et al.Model of Diameter Distribution under Selective Cutting Operation[J]. Journal of Northeast Forestry University, 2009, 37(9): 22-24.
[21] 崔秋丽. 基于人工蜂群算法的微网并网优化运行[J]. 系统仿真学报, 2018, 30(4): 347-355.
Cui Qiuli.Optimal Operation of Grid-connected Microgrid Based on ABC Algorithm[J]. Journal of System Simulation, 2018, 30(4): 347-355.
[22] 罗陆锋, 邹湘军, 杨洲, 等. 基于改进人工蜂群模糊聚类的葡萄图像快速分割方法[J]. 农业机械学报, 2015, 46(3): 23-28.
Luo Lufeng, Zou Xiangjun, Yang Zhou, et al.Grape Image Fast Segmentation Based on Improved Artificial Bee Colony and Fuzzy Clustering[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(3): 23-28.
[23] 黄丽宇. 基于泊位短时预测的停车换乘路径优选研究[D]. 成都: 西南交通大学, 2018.
Huang Liyu.Optimization of parking and transfer route based on berth short-term prediction[D]. Chengdu: Southwest Jiaotong University, 2018.
[24] 张泰, 屠思远, 吴滨, 等. 增强寻优能力的自适应人工蜂群算法[J]. 计算机应用研究, 2016, 33(10): 2946-2948.
Zhang Tai, Tu Siyuan, Wu Bin, et al.Adaptive artificial bee colony algorithm for enhancing search ability[J]. Application Research of Computers, 2016, 33(10): 2946-2948.
[25] 刘昱, 赵国新. 基于粒子群优化算法的无摩擦气缸结构优化[J]. 系统仿真学报, 2018, 30(9): 339-345.
Liu Yu, Zhao Guoxin.Optimization of frictionless cylinder structure based on particle swarm optimization algorithm[J]. Journal of System Simulation, 2018, 30(9): 339-345.
[26] 常芳芳. 基于改进SLP的生产车间静态设施布局研究 [D]. 重庆: 重庆大学, 2014.
Chang Fangfang.Research on static facility layout of production workshop based on improved SLP [D]; Chongqing: Chongqing University, 2014.
[27] Cordero I, Jiménez M D, Delgado J A, et al.Spatial and demographic structure of tara stands (Caesalpinia spinosa) in Peru: Influence of present and past forest management[J]. Forest Ecology and Management (S0378-1127), 2016, 377: 71-82.
[28] 郑立鑫. 含分布式电源的配电网黑启动策略研究[D]; 北京: 华北电力大学, 2017.
Zheng Lixin.Research on Black-Start Strategy of Distribution Network with Distributed Generation [D]; Beijing: North China Electric Power University, 2017.
[29] 董灵波, 孙云霞, 刘兆刚. 基于碳和木材目标的森林空间经营规划研究[J]. 北京林业大学学报, 2017, 39(1): 52-61.
Dong Lingbo, Sun Yunxia, Liu Zhaogang, Integrating carbon and timber objective into forest spatial planning management. Journal of Beijing Forestry University, 2017, 39(1): 52-61.