Optimisation algorithms for spatially constrained forest planning

doi:10.1016/j.ecolmodel.2005.10.028

IMR OpenIR

	Optimisation algorithms for spatially constrained forest planning
	Liu, GL ; Han, SJ ; Zhao, XH ; Nelson, JD ; Wang, HS ; Wang, WY
通讯作者	Liu, GL(gliu@forestecosystem.ca)
	2006-04-15
发表期刊	ECOLOGICAL MODELLING
ISSN	0304-3800
卷号	194 期号:4 页码:421-428
摘要	We compared genetic algorithms, simulated annealing and hill climbing algorithms on spatially constrained, integrated forest planning problems. There has been growing interest in algorithms that mimic natural processes, such as genetic algorithms and simulated annealing. These algorithms use random moves to generate new solutions, and employ a probabilistic acceptance/rejection criterion that allows inferior moves within the search space. Algorithms for a genetic algorithm, simulated annealing, and random hill climbing are formulated and tested on a same-sample forest-planning problem where the adjacency rule is strictly enforced. Each method was randomly started 20 times and allowed to run for 10,000 iterations. All three algorithms identified good solutions (within 3% of the highest found), however, simulated annealing consistently produced superior solutions. Simulated annealing and random hill climbing were approximately 10 times faster than the genetic algorithm because only one solution needs to be modified at each iteration. Performance of simulated annealing was essentially independent of the starting point, giving it an important advantage over random hill climbing. The genetic algorithm was not well suited to the strict adjacency problem because considerable computation time was necessary to repair the damage caused during crossover. (c) 2005 Elsevier B.V. All rights reserved.
关键词	landscape design integrated forest resource planning harvest scheduling genetic algorithms simulated annealing
DOI	10.1016/j.ecolmodel.2005.10.028
收录类别	SCI
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Ecology
WOS记录号	WOS:000236693500009
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：33[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/126134
专题	中国科学院金属研究所
通讯作者	Liu, GL
作者单位	1.Chinese Acad Sci, Inst Appl Forest Ecol, Shenyang, Peoples R China 2.Beijing Forestry Univ, Key Lab Silviculture & Conservat, Minist Educ, Beijing, Peoples R China 3.Univ British Columbia, Fac Forestry, Vancouver, BC V6T 1Z4, Canada
推荐引用方式 GB/T 7714	Liu, GL,Han, SJ,Zhao, XH,et al. Optimisation algorithms for spatially constrained forest planning[J]. ECOLOGICAL MODELLING,2006,194(4):421-428.
APA	Liu, GL,Han, SJ,Zhao, XH,Nelson, JD,Wang, HS,&Wang, WY.(2006).Optimisation algorithms for spatially constrained forest planning.ECOLOGICAL MODELLING,194(4),421-428.
MLA	Liu, GL,et al."Optimisation algorithms for spatially constrained forest planning".ECOLOGICAL MODELLING 194.4(2006):421-428.