 The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation.  Introduction to Genetic Algorithms - Page 403by S.N. Sivanandam, S. N. Deepa - 2007 - 442 pagesLimited preview - About this book
 | Xiaohua Jia, Jie Wu, Yanxiang He - Business & Economics - 2005 - 1154 pages
...problem space by following the current optimum particles[7]. PSO is an iteration-based optimal algorithm. The system is initialized with a population of random...solutions and searches for optima by updating generations. In the search process, PSO combine local information with global information, that is, a particle adjusts... | |
 | José Mira, José R. Álvarez - Computers - 2007 - 632 pages
...adjusted and usually PSO achieves better results in a faster, cheaper way compared with other methods. PSO is initialized with a population of random solutions and searches for optima by updating generations. The potential solutions, called particles, fly through the problem space by following the current optimum... | |
 | Patricia Melin, Oscar Castillo, Eduardo G. Ramírez, Witold Pedrycz - Technology & Engineering - 2007 - 855 pages
...by Eberhart and Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling [3]. PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA) [6]. The system is initialized with a population of random solutions and searches for optima by updating... | |
 | Natalio Krasnogor, Vincenzo Nicosia, Mario Pavone, David Alejandro Pelta - Computers - 2008 - 520 pages
...population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995 [14] inspired by social behavior of bird flocking or fish...initialized with a population of random solutions. There is a fitness measure present and the population is continuously updated. The search for optima... | |
 | Elena Marchiori - Computers - 2008 - 222 pages
...optimization technique developed by Eberhart and Kennedy in 1995 |10I11I12]. inspired by the social behaviour of bird flocking or fish schooling. PSO shares many...initialized with a population of random solutions (particles) and searches for optima of the given objective function by iteratively updating the positions... | |
 | Jano van Hemert - Computers - 2008 - 300 pages
...stochastic optimization technique, inspired by social behavior of bird flocking or fish schooling |13j. PSO shares many similarities with evolutionary computation...(GA). The system is initialized with a population solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution... | |
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