[1]董灵波,孙云霞,刘兆刚*.基于模拟退火算法的森林空间经营规划[J].南京林业大学学报(自然科学版),2018,42(01):133-140.[doi:10.3969/j.issn.1000-2006.201703111 ]
 DONG Lingbo,SUN Yunxia,LIU Zhaogang*.Spatial forest-management planning with simulated annealing algorithm[J].Journal of Nanjing Forestry University(Natural Science Edition),2018,42(01):133-140.[doi:10.3969/j.issn.1000-2006.201703111 ]
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基于模拟退火算法的森林空间经营规划
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《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

卷:
42
期数:
2018年01期
页码:
133-140
栏目:
研究论文
出版日期:
2018-01-31

文章信息/Info

Title:
Spatial forest-management planning with simulated annealing algorithm
文章编号:
1000-2006(2018)01-0133-08
作者:
董灵波孙云霞刘兆刚*
东北林业大学林学院,黑龙江 哈尔滨 150040
Author(s):
DONG LingboSUN Yunxia LIU Zhaogang*
College of Forestry, Northeast Forestry University, Harbin 150040, China
关键词:
森林规划 收获安排模型 邻接约束 绿量约束 均衡收获 模拟退火算法 森林可持续经营
Keywords:
Keywords:forest-management harvest scheduling model adjacency constraint green-up constraint even-flow harvest simulated annealing algorithm sustainable forest management
分类号:
S757.4
DOI:
10.3969/j.issn.1000-2006.201703111
文献标志码:
A
摘要:
【目的】评估不同空间约束形式对森林规划结果的影响,以期为我国森林资源的可持续经营提供科学依据【方法】以大兴安岭地区塔河林业局盘古林场数据为例,以模拟退火算法作为优化求解技术,建立了3种不同的森林收获安排模型(即非空间模型、单位限制模型(URM模型)和面积限制模型(ARM模型)),以定量分析不同空间约束形式对森林规划结果的影响。3类规划模型均以规划期内的最大化木材收益为目标函数,其中非空间规划模型不包含任何的空间信息; 在非空间规划模型的基础上,URM模型要求在相同规划分期内相邻林分不允许被同时采伐; 而在ARM模型中则允许相邻林分在相同规划分期内被同时采伐,但其最大连续面积应受到约束。此外,这3类规划模型还涉及收获均衡、最小采伐年龄以及采伐次数等约束。【结果】模拟结果表明,模拟退火算法的优化结果具有较好的稳定性,其平均变异系数仅为0.06%~3.97%,因此该算法能够适应复杂的森林规划问题。与非空间规划问题相比,当加入ARM约束时,平均目标函数值虽略有增加(0.08%),但差异不显著(P=0.35); 而当加入URM模型时,平均目标函数值显著下降约5.11%(P<0.01),但森林经营措施的时空分布更为合理。最优森林经营方案表明各规划分期的平均采伐面积均相对较小,平均仅占总面积的0.44%,能够满足森林可持续经营的需求。【结论】空间约束不仅增加了森林规划模型的复杂性,而且也在很大程度上降低了森林经营的木材收益,但其输出结果更符合森林可持续经营的理念。同时,以模拟退火算法为代表的启发式算法能够满足复杂森林规划问题的需求。
Abstract:
【Objective】 Harvest adjacency and green-up constraints have become the most commonly used constraint types for spatial forest harvest scheduling in forestry in developed countries worldwide in the last decade; however, few studies have focused on this issue in our country. Therefore, the concept of this forest-management technique will be discussed thoroughly with an example from Northeast China, which can provide certain insights into the sustainable management of forest ecosystems in our country. 【Method】 Using a simulated annealing algorithm as an optimization technique, three increasingly difficult forest-planning problems were analyzed for the Pangu Forest Farm in the Da Hinggan Ling Prefecture, Northeast China, which were used for analyzing the effects of different spatial constraint types on the results of forest planning. The objective functions for all three planning problems were to maximize the discounted net present value of forest ecosystems for timber production. The first problem, a non-spatial problem, did not include any spatial information. However, the second and third problems, i.e., the unit restriction model(URM)and area restriction model(ARM)problems, were analyzed based on the non-spatial problem. The URM problem strictly prohibited the scheduling of neighboring management units for a final harvest during the same period; however ARM allowed for the scheduling of certain limited neighboring units for final harvest during the same period, provided that the total final-harvest area was less than the user-defined maximum size. Additionally, all three planning problems were subjected to the even-flow harvest constraint, green-up constraint, minimum harvest-age constraint and number of harvest constraints for each unit(or stand). 【Result】 The results showed that the coefficient of variation of the objective function values for each planning problem only ranged from 0.06% to 3.97%, indicating the great stability of the simulated annealing algorithm. The objective function values of the ARM problems increased slightly(0.08%),although not significantly(P=0.35), and those of the URM problems reduced significantly(5.11%, P<0.01),compared with those of the non-spatial problem; however, the temporal and spatial outputs of the forest management treatment became more reasonable. The percentage of all harvest areas across the planning horizon of the optimal forest-management plan for each planning period was relative less, only accounting for approximately 0.44% of the total area in the forest dataset. These results were reasonably and perfectly consistent with the criteria of sustainable forest management. 【Conclusion】 The spatial constraints for forest-management treatments increase the complexity of forest-planning models, and significantly decrease the economic benefits of timber production from forest ecosystems, as well; however, the outputs of forest-management plans might be more suitable for sustainable forest management. Additionally, most heuristic techniques, including simulated annealing algorithms, can be applied to larger and more complex forest-planning problems, as performed in this study.

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备注/Memo

备注/Memo:
基金项目:国家自然科学基金项目(31700562); 东北林业大学“双一流”人才引进项目(2017) 第一作者:董灵波(farrell0503@126.com),讲师,博士。*通信作者:刘兆刚(lzg19700602@163.com),教授,博士。
更新日期/Last Update: 2018-03-30