The Case Study of Swarm Intelligence Optimization Algorithm Performance
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 8
Abstract
This paper was study in swarm intelligence optimization algorithm performance nature-inspired meta-heuristic algorithm, especially those based on swarm intelligence. Have attracted much attention in the algorithm Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Bacterial Foraging Optimization (BFO). In propose to application to optimization self-experiences with social experiences. Agents moving around in the best solution for search. Examples include flocks of birds, colonies of ants, and E. coli & Chemo taxis. Such intelligence is decentralized, self-organizing and distribution throughout an environment. Functions show that the convergences speed and accuracy of the algorithm.
Authors and Affiliations
Jancy Rani. M, Elangovan. K, Sheela Rani. T
Keywords
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