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Electromagnetic optimization using a mixed‐parameter self‐adaptive evolutionary algorithm
Author(s) -
Hoorfar Ahmad,
Zhu Jinhui,
Nelatury Sudarshan
Publication year - 2003
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.11187
Subject(s) - gaussian , evolutionary algorithm , poisson distribution , algorithm , mutation , operator (biology) , adaptive mutation , genetic programming , mathematical optimization , distribution (mathematics) , constraint (computer aided design) , representation (politics) , evolutionary programming , filter (signal processing) , computer science , genetic algorithm , mathematics , physics , artificial intelligence , statistics , mathematical analysis , quantum mechanics , repressor , law , chemistry , biochemistry , political science , transcription factor , politics , gene , geometry , computer vision
An evolutionary programming algorithm with a mixed continuous‐discrete parameter representation for application in electromagnetic optimization problems is presented. In our approach, the mutation operator consists of a hybrid combination of Gaussian mutation for the continuous parameters, and Poisson mutation for the discrete parameters. The implementation uses self‐adaptive schemes for updating the standard deviation of the Gaussian distribution and the mean of the Poisson distribution during the evolution. As an example, the proposed evolutionary algorithm is applied to the constraint designs of various multilayer dielectric‐filter structures. © 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 39: 267–271, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.11187