An Immunity Based Hybrid Evolutionary Algorithm for Engineering Optimization

淡江大學機構典藏 > 工學院 > 機械與機電工程學系暨研究所 > 期刊論文 > Item 987654321/52790

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题名:	An Immunity Based Hybrid Evolutionary Algorithm for Engineering Optimization
作者:	史建中;Shih, Chien-jong;Kuan, T. L.
贡献者:	淡江大學機械與機電工程學系
关键词:	Biological Computation;Artificial Immune System;Evolutionary Algorithm;Engineering Optimization;Structural Design
日期:	2006-03
上传时间:	2010-12-01 10:31:18 (UTC+8)
出版者:	臺北縣：淡江大學
摘要:	The immune system has been recognized possesses pattern recognition ability in which the lymphocytes can learn to distinguish selves and match a variety of pathogens. Consequently, sufficient antibodies are generated to eliminate the growth of the foreign antigens. This paper describes the inspiration from the immune system and how to apply immune system principles to develop the global unconstrained and constrained optimization algorithms. The features of the proposed approach contain: the affinity maturation in immune system has been employed as the primary principle, the real number code has been used as genes representation in this development; the modified expression strategy for constraints handling and a diverse multiplication generated in genetic algorithm. Numerical structural engineering optimization problems demonstrate that the proposed immunity based evolutionary approach has the solution consistency; avoiding premature and can achieve a robust final design.
關聯:	淡江理工學刊=Tamkang journal of science and engineering 9(1)，頁25-36
显示于类别:	[機械與機電工程學系暨研究所] 期刊論文

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