標題: Inductive linkage identification on building blocks of different sizes and types
作者: Chen, Ying-ping
Chuang, Chung-Yao
Huang, Yuan-Wei
資訊工程學系
Department of Computer Science
關鍵字: inductive linkage identification;ILI;linkage learning;BBs;genetic algorithms;evolutionary computation
公開日期: 2012
摘要: The goal of linkage identification is to obtain the dependencies among decision variables. Such information or knowledge can be applied to design crossover operators and/or the encoding schemes in genetic and evolutionary methods. Thus, promising sub-solutions to the problem will be disrupted less likely, and successful convergence may be achieved more likely. To obtain linkage information, a linkage identification technique, called Inductive Linkage Identification (ILI), was proposed recently. ILI was established upon the mechanism of perturbation and the idea of decision tree learning. By constructing a decision tree according to decision variables and fitness difference values, the interdependent variables will be determined by the adopted decision tree learning algorithm. In this article, we aim to acquire a better understanding on the characteristics of ILI, especially its behaviour under problems composed of different-sized and different-type building blocks (BBs) which are not overlapped. Experiments showed that ILI can efficiently handle BBs of different sizes and is insensitive to BB types. Our experimental observations indicate the flexibility and the applicability of ILI on various elementary BB types that are commonly adopted in related experiments.
URI: http://hdl.handle.net/11536/20510
http://dx.doi.org/10.1080/00207721.2011.566639
ISSN: 0020-7721
DOI: 10.1080/00207721.2011.566639
期刊: INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Volume: 43
Issue: 12
起始頁: 2202
結束頁: 2213
顯示於類別:期刊論文


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