A Review on Microstrip Antenna Optimization using Bio-Inspired Optimization Techniques
Ankita R Suvagia

Ankita R Suvagia, Department of Electronics & Communication, Parul Institute of Engineering & Technology, Limda Vaghodia, Baroda (Gujarat), India.
Manuscript received on 20 May 2014 | Revised Manuscript received on 25 May 2014 | Manuscript published on 30 May 2014 | PP: 20-22 | Volume-3 Issue-2, May 2014 | Retrieval Number: B1076053214/2014©BEIESP
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Abstract: Soft computing techniques like neural network, genetic and other optimization techniques proved to be an effective way to solve the problem of getting optimum value of antenna parameters for a particular frequency band. It provides a solution for high dimension problems with multiple local optima. Parameters like gain, return loss and directivity are optimized for a microstrip antenna. This paper highlights the implementation of neural network and other bio-inspired optimization techniques like Particle –Swarm Optimization (PSO), Differential Evolution (DE) Techniques and Genetic Algorithm on Microstrip antenna Dimensions which results in better Performance.
Keywords: Optimization, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Biogeographic – Based Optimization (BBO).

Scope of the Article: Data Mining Methods, Techniques, and Tools