TY  - CHAP
AU  - Shahab Mohammad-Moradi
AU  - Hamid Khaloozadeh
AU  - Mohamad Forouzanfar
AU  - Ramezan Paravi Torghabeh
AU  - Nosratallah Forghani
ED  - Aleksandar Lazinica
Y1  - 2009-01-01
PY  - 2009
T1  - Swarm Intelligence in Portfolio Selection
N2  - Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). 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. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field.
BT  - Particle Swarm Optimization
SP  - Ch. 13
UR  - https://doi.org/10.5772/6750
DO  - 10.5772/6750
SN  - 
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-26
ER  -