Particle swarm optimization: technique, system and challenges

• Main Authors: Rini, Dian Palupi, Shamsuddin, Siti Mariyam, Yuhaniz, Siti Sophiyati
• Format: Article
• Published: International Journal of Computer Applications 2011
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/39954/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:77902
• Institution: Universiti Teknologi Malaysia

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other hand, basic PSO is more appropriate to process static, simple optimization problem. Modification PSO is developed for solving the basic PSO problem. The observation and review 46 related studies in the period between 2002 and 2010 focusing on function of PSO, advantages and disadvantages of PSO, the basic variant of PSO, Modification of PSO and applications that have implemented using PSO. The application can show which one the modified or variant PSO that haven’t been made and which one the modified or variant PSO that will be developed.