Adjacency Branches Used To Optimize Forest Harvesting Subject to Area Restrictions on Clearfell

IF 1.5 4区 农林科学 Q2 FORESTRY Forest Science Pub Date : 2024-04-10 DOI:10.1093/forestscience/54.4.442
Alastair J. McNaughton, David Ryan
{"title":"Adjacency Branches Used To Optimize Forest Harvesting Subject to Area Restrictions on Clearfell","authors":"Alastair J. McNaughton, David Ryan","doi":"10.1093/forestscience/54.4.442","DOIUrl":null,"url":null,"abstract":"Consider a forest containing units of various sizes for which a maximum clearfell area has been specified along with an associated green-up time period. For such an application it is customary to use adjacency constraints to produce a harvesting plan. These constraints control the availability for harvest of specific units relative to the harvesting of certain adjacent units. However, such constraints are difficult to formulate and often precipitate major difficulties in the implementation of the solution algorithm. A new concept, a nuclear set, is introduced. This concept allows the unit-specific aspects of the problem to be analyzed in an insightful manner. Any adjacency violation can be detected in relation to these nuclear sets. Suitable adjacency branches can be implemented to remove these violations. The form of these branches derives from the same nuclear sets. A remarkably small number of these branches are required to obtain a feasible solution. These ideas are incorporated into a column generation and constraint generation model. This new forest harvesting model solves the clearfell area restriction problem in an exact sense. Results are included for numerical trials involving simulated data representing moderately sized applications with a planning horizon of up to one rotation. The output from these trials suggests that this algorithm is suitable for large commercial applications. Several applications of 1,600 units are solved over 25 time periods with multiple green-up.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forest Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1093/forestscience/54.4.442","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 0

Abstract

Consider a forest containing units of various sizes for which a maximum clearfell area has been specified along with an associated green-up time period. For such an application it is customary to use adjacency constraints to produce a harvesting plan. These constraints control the availability for harvest of specific units relative to the harvesting of certain adjacent units. However, such constraints are difficult to formulate and often precipitate major difficulties in the implementation of the solution algorithm. A new concept, a nuclear set, is introduced. This concept allows the unit-specific aspects of the problem to be analyzed in an insightful manner. Any adjacency violation can be detected in relation to these nuclear sets. Suitable adjacency branches can be implemented to remove these violations. The form of these branches derives from the same nuclear sets. A remarkably small number of these branches are required to obtain a feasible solution. These ideas are incorporated into a column generation and constraint generation model. This new forest harvesting model solves the clearfell area restriction problem in an exact sense. Results are included for numerical trials involving simulated data representing moderately sized applications with a planning horizon of up to one rotation. The output from these trials suggests that this algorithm is suitable for large commercial applications. Several applications of 1,600 units are solved over 25 time periods with multiple green-up.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
邻接枝条用于优化森林采伐,但受开伐面积限制
考虑一个包含不同大小单位的森林,其中规定了最大的采伐面积和相关的绿化时间段。在这种应用中,通常使用相邻约束条件来制定采伐计划。这些约束条件可以控制特定单位的采伐量与某些相邻单位的采伐量。然而,这种约束很难制定,而且往往会给求解算法的实施带来很大困难。我们引入了一个新概念--核集。通过这一概念,可以对问题的特定单元方面进行深入分析。任何违反邻接关系的情况都可以根据这些核集进行检测。可以实施适当的邻接分支来消除这些违规行为。这些分支的形式源自相同的核集。要获得一个可行的解决方案,只需要极少量的这些分支。这些想法被纳入了列生成和约束生成模型。这种新的森林采伐模型从精确的意义上解决了伐木区限制问题。模型中包含了模拟数据的数值试验结果,这些数据代表了中等规模的应用,规划期限最长为一个轮伐期。试验结果表明,该算法适用于大型商业应用。在 25 个时间段内,通过多次绿化,解决了 1,600 个单位的若干应用问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Forest Science
Forest Science 农林科学-林学
CiteScore
2.80
自引率
7.10%
发文量
45
审稿时长
3 months
期刊介绍: Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management. Forest Science is published bimonthly in February, April, June, August, October, and December.
期刊最新文献
Selective Postplanting Forb Control Increased Growth of Douglas-Fir but Not Western Larch Seedlings in Idaho Accuracy of Whitebark Pine and Limber Pine Identification by Forest Inventory and Analysis Field Crews Applying Ratio-of-Means Estimation for Annualized Components of Volume Change in Forest Resource Monitoring Genetic Variability for Clonal Propagation of Acacia mearnsii Whole-Tree Green Density Equations for Loblolly and Slash Pine Trees
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1