Antenna Design Using an Enhanced Multi‐Objective Artificial Hummingbird Algorithm Based on Tolerance Mechanism

ABSTRACT This letter presents a tolerance mechanism‐based enhanced multi‐objective artificial hummingbird algorithm (TM‐EMOAHA) for antenna optimization. The proposed method introduces an improved Pareto non‐dominated solution determination strategy with a tolerance mechanism to precisely define dom...

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Bibliographic Details
Published in:Microwave and optical technology letters Vol. 67; no. 9
Main Authors: Huang, Guan‐Long, He, Jin‐Peng, Qin, Peng‐Fei, Pang, Zi‐Yu, He, Xian‐Hui, Mahmoud, Abdelhady, Zeng, Jingtao, Yang, Hua
Format: Journal Article
Language:English
Published: New York Wiley Subscription Services, Inc 01.09.2025
Subjects:
Algorithms
Antenna design
antenna optimization
artificial hummingbird algorithm
Coordinate transformations
multi‐objective
Patch antennas
Polar coordinates
series‐fed patch antenna
Sidelobes
tolerance mechanism
ISSN:0895-2477, 1098-2760
Online Access:Get full text
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Summary:ABSTRACT This letter presents a tolerance mechanism‐based enhanced multi‐objective artificial hummingbird algorithm (TM‐EMOAHA) for antenna optimization. The proposed method introduces an improved Pareto non‐dominated solution determination strategy with a tolerance mechanism to precisely define dominance relationships through objective prioritization. A hybrid perturbation strategy integrating polar coordinate transformation and objective‐oriented guidance is developed to enhance global search capability. The algorithm's effectiveness is demonstrated through a series‐fed patch antenna design case. Experimental results validate that compared with traditional multi‐objective algorithms, the TM‐EMOAHA obtains a series‐fed patch antenna with higher gain characteristics and lower sidelobe.
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ISSN:0895-2477
1098-2760
DOI:10.1002/mop.70384