TY - JOUR
T1 - Swarm intelligence in multiple and many objectives optimization
T2 - A survey and topical study on EEG signal analysis
AU - Mishra, B. S.P.
AU - Dehuri, Satchidanand
AU - Cho, Sung Bae
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2015.
PY - 2015
Y1 - 2015
N2 - This paper systematically presents the Swarm Intelligence (SI) methods for optimization of multiple and many objective problems. The fundamental difference of Multiple and Many Objective Optimization problems have been studied very rigorously. The three forefront swarm intelligence methods, i.e., Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony Optimization (ABC) has been deeply studied to understand their ways of solving multiple and many objective problems distinctly. A pragmatic topical study on the behavior of real ants, bird flocks, and honey bees in solving EEG signal analysis completes the survey followed by discussion and extensive number of relevant references.
AB - This paper systematically presents the Swarm Intelligence (SI) methods for optimization of multiple and many objective problems. The fundamental difference of Multiple and Many Objective Optimization problems have been studied very rigorously. The three forefront swarm intelligence methods, i.e., Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony Optimization (ABC) has been deeply studied to understand their ways of solving multiple and many objective problems distinctly. A pragmatic topical study on the behavior of real ants, bird flocks, and honey bees in solving EEG signal analysis completes the survey followed by discussion and extensive number of relevant references.
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U2 - 10.1007/978-3-662-46309-3_2
DO - 10.1007/978-3-662-46309-3_2
M3 - Article
AN - SCOPUS:84924961653
SN - 1860-949X
VL - 592
SP - 27
EP - 73
JO - Studies in Computational Intelligence
JF - Studies in Computational Intelligence
ER -