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Multi-Objective Optimization Algorithm Develpoment using Chaotic Maps to Design of a Planar Microstrip Monopole Antenna

Year: 2025

Type: article

Abstract: This research uses a new multi-objective optimization algorithm to design a single pole antenna with specific electromagnetic characteristics. This algorithm uses a hybrid chaotic function to integrate the customized mutated particle swarm algorithm with the modified genetic algorithm. By avoiding getting trapped in local minima, the new hybrid approach achieves desired results faster than conventional particle swarm algorithms and genetic algorithms. The performance of the proposed meta-heuristic algorithm has been successfully simulated and stabilized using benchmark functions such as Rastrigen's function, Ackley's function, Rosenbrook's function, and Booth's function. Finally, the validity of the presented approach for electromagnetic applications is demonstrated by optimizing a planar microstrip monopole antenna with a simple structure. The proposed algorithm allows the optimization criteria to be customized to achieve the predetermined results for return loss and resonance frequency. The optimization algorithm developed in MATLAB is used to determine the necessary parameter settings in order to achieve the expected frequency bands using custom mutated particle swarm algorithm or heuristic modified genetics. The dimensions of the proposed antenna elements significantly affect the antenna performance.

Source: DOAJ (DOAJ: Directory of Open Access Journals)

Authors: Vahid Hosseini, Yousef Farhang, Kambiz Majidzadeh, Changiz Ghobadi

Institutions: Payame Noor University, İstanbul Esenyurt Üniversitesi, Islamic Azad University of Urmia, Urmia University

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6992950762

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