Swarm, Evolutionary, and Memetic Computing

Volume 6466 of the series Lecture Notes in Computer Science pp 163-170

Expedite Particle Swarm Optimization Algorithm (EPSO) for Optimization of MSA

  • Amit RathiAffiliated withDepartment of Electronics, Banasthali University
  • , Ritu VijayAffiliated withDepartment of Electronics, Banasthali University

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This paper presents a new designing method of Rectangular patch Microstrip Antenna using an Artificial searches Algorithm with some constraints. It requires two stages for designing. In first stage, bandwidth of MSA is modeled using bench Mark function. In second stage, output of first stage give to modified Artificial search Algorithm which is Particle Swarm Algorithm (PSO) as input and get output in the form of five parameter- dimensions width, frequency range, dielectric loss tangent, length over a ground plane with a substrate thickness and electrical thickness. In PSO Cognition, factor and Social learning Factor give very important effect on balancing the local search and global search in PSO. Basing the modification of cognition factor and social learning factor, this paper presents the strategy that at the starting process cognition-learning factor has more effect then social learning factor. Gradually social learning factor has more impact after learning cognition factor for find out global best. The aim is to find out under above circumstances these modifications in PSO can give better result for optimization of microstrip Antenna (MSA).


Artificial Search Algorithm inverse modeling Particle Swarm Optimization Cognition Factor Social Learning Factor Local Search and Global Search