Optimal Sizing of Integrated Inductor using a Hybrid Optimization Algorithm

This paper proposes a hybridization of Differential Evolution algorithm (DE) and Ant Colony Optimization algorithm (ACO) named DE-ACO. The proposed algorithm has been evaluated in terms of solution quality, robustness, and computation time using three well-known benchmark functions. In addition, the...

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Bibliographic Details
Published in2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) pp. 1 - 6
Main Authors Abi, Soufiane, Benhala, Bachir
Format Conference Proceeding
LanguageEnglish
Published IEEE 03.03.2022
Subjects
Ant colony optimization
Benchmark Functions
Benchmark testing
Computational modeling
Differential Evolution
Hybrid Metaheuristic Algorithm
Integrated Inductors
Metaheuristics
Q-factor
Robustness
Spirals
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DOI10.1109/IRASET52964.2022.9737884

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Summary:This paper proposes a hybridization of Differential Evolution algorithm (DE) and Ant Colony Optimization algorithm (ACO) named DE-ACO. The proposed algorithm has been evaluated in terms of solution quality, robustness, and computation time using three well-known benchmark functions. In addition, the DE-ACO algorithm was applied to generate the optimal geometrical parameters of a square spiral inductor to obtain better performance in terms of quality factor. EM simulations were performed using ADS Momentum to validate the obtained results.
DOI:10.1109/IRASET52964.2022.9737884