Title :
Particle Swarm Optimization with varying Inertia Weight for solving nonlinear optimization problem
Author :
Braj Bhushan Pandey ; Debbarma, Swapan ; Bhardwaj, Prashant
Author_Institution :
Department of Computer Science and Engineering, National Institute of Technology Agartala, India
Abstract :
This paper focuses on performance studies of various variants of Inertia weights (w) of Particle Swarm Optimization (PSO). PSO is a metaheuristics optimization technique used for solving various complex optimization problems. It has various parameters to control its processing. Among those a very crucial one is Inertia Weight which is being used for controlling the velocity of the particle. In this paper a new concept of Inertia Weight is being introduced which is a function of previous inertia weight and is also dependent on previous local best values as well as global best values
Keywords :
Artificial neural networks; Birds; Computer science; Genetic algorithms; Mathematical model; Optimization; Particle swarm optimization; PSO; decreasing inertia weight; increasing inertia weight; oscillating inertia weight;
Conference_Titel :
Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015 International Conference on
Conference_Location :
Visakhapatnam, India
Print_ISBN :
978-1-4799-7676-8
DOI :
10.1109/EESCO.2015.7253658
