Arithmetic adopted chimp optimisation algorithm for optimal MPA design

Meena Chavan, B. Bhuvaneswari and J.V.N. Ramesh

International Journal of Industrial and Systems Engineering, 2025, vol. 51, issue 3, 283-308

Abstract: Presently, MPAs are often used in a number of appliances due to their properties like lightweight, compatibility, reduced volume, low cost, and ease of installation on hard surfaces. Optimal antenna design ensures better results in almost all applications. Hence, this paper aims to introduce a novel Microstrip patch antenna design optimisation that ensures enhanced antenna performance with the optimal design parameters like substrate thickness, width, height, and length, under the satisfaction of multi-objectives like gain, bandwidth, antenna efficiency, return loss, and TARC. To solve the given optimisation problem, this work implements an arithmetic adopted chimp optimisation algorithm (AAChOA) scheme that merges the strategy of the chimp optimisation algorithm (ChOA) and arithmetic optimisation algorithm (AOA) to obtain higher antenna performance. Finally, the proposed technique was evaluated over other extant models based on different parameters like antenna gain, efficiency, total active reflection coefficient (TARC), return loss, and bandwidth.

Keywords: microstrip patch antenna; MPA; antenna efficiency; return loss; gain; optimisation. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=149944 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:51:y:2025:i:3:p:283-308

Access Statistics for this article

More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().