NDLI: A novel genetic algorithm based on immunity and its application

Content Provider	IEEE Xplore Digital Library
Author	Fengqiang Zhao Guangqiang Li Jialu Du Chen Guo Hongying Hu Abraham, A.
Copyright Year	2012
Description	Author affiliation: School of Information Science and Technology, Dalian Maritime University, 116026, China (Fengqiang Zhao; Guangqiang Li; Jialu Du; Chen Guo) \|\| Machine Intelligence Research Labs, Scientific Network for Innovation and Research Excellence, WA, USA (Abraham, A.) \|\| School of Electromechanical & Information Engineering, Dalian Nationalities University, 116600, China (Hongying Hu)
Abstract	In this paper, a novel genetic algorithm based on immunity (GABI) on the basis of parallel genetic algorithms (PGA) is proposed in order to overcome some defects of them, such as premature and slow convergence rate. The global performance of the algorithm is improved by introducing immunity theory into PGA. This is revealed in the following two aspects. One is that the immune selection based on proposed adjustable geometric-progression rank-based selection can prevent the algorithm from premature. The other is that convergence rate can be accelerate by individual migration strategy between subpopulations based on immune memory mechanism. In this algorithm, the idea of multiple subpopulations evolution based on improved adaptive crossover and mutation is adopted. To be hybridized with the Powell method can further improve local searching performance of the algorithm. An example of layout design shows that GABI is feasible and effective.
Starting Page	566
Ending Page	571
File Size	255088
Page Count	6
File Format	PDF
ISBN	9781467351140
e-ISBN	9781467351164
DOI	10.1109/HIS.2012.6421396
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-04
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	layout Layout Sociology genetic algorithms immunity hybrid methods Statistics parallel computing Genetic algorithms Immune system Electronics packaging Convergence
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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