NDLI: Improved Cultural Algorithm based on Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Zhengui Xue Yinan Guo
Copyright Year	2007
Description	Author affiliation: South China Univ. of Technol., Guangzhou (Zhengui Xue)
Abstract	Knowledge about evolutionary information is not made use of effectively in genetic algorithm. While traditional cultural algorithms with dual inheritance structure converge slowly because evolutionary programming is chosen for the population model and only mutation operator is adopted in the population space. A novel cultural algorithm based on genetic algorithm is proposed. Four kinds of knowledge are abstracted. Simulation results on the benchmark single-peak optimization functions indicate that the performance of this method is much better than traditional cultural algorithms especially for the "plain functions". Aiming at multi-peaks optimization problem, multi-windows cultural algorithm and multi-windows cultural algorithm based on genetic algorithm are introduced. Simulation results on benchmark multi-peaks function indicates that the latter is more effective in optimization performance than the former.
Starting Page	117
Ending Page	122
File Size	1626185
Page Count	6
File Format	PDF
ISBN	1424410916
DOI	10.1109/ICITECHNOLOGY.2007.4290443
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Automation Genetic mutations Multi-Windows Evolutionary computation Genetic Algorithm Cultural Algorithm Cultural differences Genetic algorithms Convergence Genetic programming Production Evolutionary Programming Global communication Problem-solving
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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