NDLI: The enhanced genetic algorithms for the optimization design

Content Provider	IEEE Xplore Digital Library
Author	Pengfei Guo Xuezhi Wang Yingshi Han
Copyright Year	2010
Description	Author affiliation: School of Civil and Architectural Engineering, Liaoning University of Technology, Jinzhou 121001, China (Pengfei Guo; Xuezhi Wang; Yingshi Han)
Abstract	Three different kinds of the novel enhanced genetic algorithm procedures including the hybrid genetic algorithm, interval genetic algorithm and hybrid interval genetic algorithm are respectively presented. As the results of the proven systems show, the hybrid genetic algorithm can determines the better optimum design than the traditional optimization algorithms and genetic algorithm. The interval genetic algorithm and hybrid interval genetic algorithm can avoid calculating system slope in traditional interval analysis and determines the optimum interval range of the parameters under allowable corresponding objective error boundary. It is the first time that genetic algorithm has been applied to interval optimization process.
Starting Page	2990
Ending Page	2994
File Size	331694
Page Count	5
File Format	PDF
ISBN	9781424464951
e-ISBN	9781424464982
DOI	10.1109/BMEI.2010.5639829
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Gallium hybrid genetic algorithm hybrid interval genetic algorithm optimization Genetics Polynomials genetic algorithms interval genetic algorithm Optimization Biological cells Genetic algorithms
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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