TY  - JOUR
AU  - Nakisa, Bahareh 
AU  - Nazri, Mohd Zakree Ahmad 
AU  - Rastgoo, Mohammad Naim 
AU  - Abdullah, Salwani 
PY  - 2014
TI  - A SURVEY: PARTICLE SWARM OPTIMIZATION BASED ALGORITHMS TO SOLVE PREMATURE CONVERGENCE PROBLEM
JF  - Journal of Computer Science
VL  - 10
IS  - 9
DO  - 10.3844/jcssp.2014.1758.1765
UR  - https://thescipub.com/abstract/jcssp.2014.1758.1765
AB  - 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.