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

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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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