A SURVEY: PARTICLE SWARM OPTIMIZATION BASED ALGORITHMS TO SOLVE PREMATURE CONVERGENCE PROBLEM
Bahareh Nakisa, Mohd Zakree Ahmad Nazri, Mohammad Naim Rastgoo and Salwani Abdullah
DOI : 10.3844/jcssp.2014.1758.1765
Journal of Computer Science
Volume 10, Issue 9
Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, we include a classification of the approaches and we identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.
© 2014 Bahareh Nakisa, Mohd Zakree Ahmad Nazri, Mohammad Naim Rastgoo and Salwani Abdullah. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.