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Constrained minimization utilizing GA based pattern recognition of immune system

Authors
 Jongsoo Lee  ;  Hyuk Park 
Citation
 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, Vol.21(5) : 779-788, 2007 
Journal Title
 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 
ISSN
 1738-494X 
Issue Date
2007
Abstract
The immune system has pattern recognition capabilities based on reinforced learning, memory and affinity maturation interacting between antigens and antibodies. The paper deals with the adaptation of artificial immune system into genetic algorithm based design optimization. The present study utilizes the pattern recognition from the immune system and the evolution from genetic algorithm. The basic idea is derived from the fact that designs should be distinguished whether they are usable/feasible or infeasible and should be improved towards the optimal solution. For the expression of design solutions, binary coded strings are used to represent antigens and antibodies in artificial immune system and chromosomes in genetic algorithm. The paper discusses the procedure of constrained optimization that does not rely on any detailed mathematical formulation for constraint handling. A number of mathematical function minimization problems are examined for verification, and practical engineering optimization problems including inequality constraints are explored to support the proposed strategy.
Full Text
http://link.springer.com/article/10.1007%2FBF02916356
DOI
10.1007/BF02916356
Appears in Collections:
2. College of Dentistry (치과대학) > Dept. of Oral and Maxillofacial Radiology (영상치의학교실) > 1. Journal Papers
Yonsei Authors
Park, Hyuk(박혁)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/96473
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