A novel particle swarm optimisation algorithm for continuous function optimisation. (1st January 2012)

• Record Type: Journal Article
• Authors: Rameshkumar, K.; Rajendran, Chandrasekharan; Mohanasundaram, K.M.
• Is Part Of: International journal of operational research. Volume 13:Number 1(2012)
• Page Start: 1
• Page End: 21
• Publication Date: 2012-01-01
• Subjects: particle swarm optimisation algorithm -- dynamic velocity updating -- local search scheme -- continuous function optimisation; Operations research -- Periodicals; 003.05
• DOI: 10.1504/IJOR.2012.044025
• Languages: English
• ISSNs: 1745-7645

Abstract

Particle swarm optimisation (PSO) algorithms are applied in a variety of fields. A good quality solution for a problem depends on the PSO parameters chosen for the problem under study. In this paper, a continuous particle swarm optimisation algorithm is proposed to solve the unconstrained optimisation problems. This paper proposes a novel and simple variation of the PSO algorithm by introducing dynamic updating of velocity without any parameters, such as inertia weight and constriction coefficients that are commonly used in the traditional PSO algorithms. The proposed algorithm is applied to well-known benchmark functions which are commonly used to test the performance of numeric optimisation algorithms, and the results are compared with the existing PSO algorithms. It is found that the proposed algorithm gives superior results in terms of speed of convergence and the ability of finding the solutions of excellent quality.