Augmented Genetic Algorithm V3 for Multi-Objective Pdn Decap Optimization
Abstract
This paper proposes a novel approach for generating the initial population, termed disproportionate initialization, to enhance the genetic algorithm's efficiency in optimizing the number of decaps. This method is specifically designed to accelerate convergence, improving the algorithm's ability to find optimal solutions. The algorithm is improved to simultaneously reduce the number of decoupling capacitors and achieve the lowest cost, aiming to identify the global minima for comprehensive PDN optimization.
Recommended Citation
H. Manoharan et al., "Augmented Genetic Algorithm V3 for Multi-Objective Pdn Decap Optimization," 2024 IEEE Joint International Symposium on Electromagnetic Compatibility, Signal and Power Integrity: EMC Japan/Asia Pacific International Symposium on Electromagnetic Compatibility, EMC Japan/APEMC Okinawa 2024 - Proceedings, pp. 560 - 563, Institute of Electrical and Electronics Engineers, Jan 2024.
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
decap optimization; disproportionate initial population; Multi-Objective Genetic Algorithm; population diversity
International Standard Book Number (ISBN)
978-488552347-2
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2024
Comments
National Science Foundation, Grant IIP-1916535