Work place: D Y Patil Institute of Engineering and Technology, Pune, University of Pune, Maharashtra, India
E-mail: snehal_kamalapur@yahoo.com
Website:
Research Interests: Computer systems and computational processes, Evolutionary Computation, Pattern Recognition, Swarm Intelligence
Biography
Mrs. Snehal Kamalapur received ME (Computer Engineering) degrees from University of Pune 2003. She is working as associate professor in the K K Wagh Institute of Engineering Education and Research, University of Pune. She is currently pursuing PhD from university of Pune. She has published over 28 research papers in conferences and Journals. She is life member of various professional bodies. Her research interests include swarm intelligence, evolutionary computation and pattern recognition.
By Snehal Mohan Kamalapur Varsha Hemant Patil
DOI: https://doi.org/10.5815/ijisa.2015.01.06, Pub. Date: 8 Dec. 2014
Particle Swarm Optimization is swarm based optimization technique. Swarm consists of particles and the particles fly through the problem space in Particle Swarm Optimization (PSO). Confinement methods and parameters such as Inertia Weight, Neighborhood of the particle have major impact on PSO performance. The paper presents variations of the PSO with adaptive random link neighborhood. The work carried out considers linearly decreasing inertia weight and different confinement methods. The performance of adaptive random link PSO by geometrical updation of velocity with confinement methods is tested here.
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