Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems

Articles in Press

Document Type : Research Article

Authors

• ABDELBARI falloun ¹
• Yunus Dursun ²
• Abdessalam Ait Madi ¹

¹ Advanced Systems Engineering Laboratory, National School of Applied Sciences, Ibn Tofail University, Kenitra, Morocco.

² Electrical and electronic engineering, Marmara University, Istanbul, Türkiye.

10.22067/ijnao.2024.86247.1371

Abstract

Particle swarm optimization (PSO) is a widely recognized bio-inspired algorithm for systematically exploring solution spaces and iteratively identifying optimal points. Through updating local and global best solutions, PSO effectively explores the search process, enabling the discovery of the most advantageous outcomes. This study proposes a novel Smith chart-based particle swarm optimization (SC-PSO) to solve convex and non-convex multi-objective engineering problems by representing complex plane values in a polar coordinate system. The main contribution of this paper lies in the utilization of the Smith chart’s impedance and admittance circles to dynamically update the location of each particle, thereby effectively determining the local best particle. The proposed method is applied to three test functions with different behaviors, namely concave, convex, non-continuous, and non-convex, and performance parameters are examined. The simulation results show that the proposed strategy offers successful convergence performance for multi-objective optimization applications and meets performance expectations with a well-distributed solution set.

Keywords

• Multi-objective optimization (MOO)
• particle swarm optimization (PSO)
• meta-heuristic optimization

Main Subjects

• Control and Optimization

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