Rathi A., Vijay R. (2010) Expedite Particle Swarm Optimization Algorithm (EPSO) for Optimization of MSA. In: Panigrahi B.K., Das S., Suganthan P.N., Dash S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2010. Lecture Notes in Computer Science, vol 6466. Springer, Berlin, Heidelberg
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