Cognitive and social information based PSO

Abstract

In 1995 swarm intelligence based PSO (Particle Swarm Optimization) has been designed and implemented for solving optimization problems. Since then many researchers have developed many versions, based upon its theoretical concept, technical aspects and parameters involve in the algorithm. In broad sense, every swarm updates its position based upon the knowledge of its initial velocity and accelerating components such as cognitive and social information. In this paper we have presented a reformed and modified concept of PSO with the thought that every swarm updates its position based upon cognitive and social environment knowledge only and the key aspect used here is that these parameters are no longer assumed to be accelerating components rather position components. This algorithm is termed by us as Cognitive and Social Information based PSO (CSIPSO). The performance of CSI-PSO is validated by 23 benchmark functions and the empirical results clearly support the effectiveness of our concept.

Keywords: Particle Swarm, PSO, Swarm Theory, Benchmark functions