Swarm intelligence in multiple and many objectives optimization: A survey and topical study on EEG signal analysis

B. S.P. Mishra, Satchidanand Dehuri, Sung Bae Cho

Research output: Contribution to journalArticle

6 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)27-73
Number of pages47
JournalStudies in Computational Intelligence
Publication statusPublished - 2015 Jan 1


All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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