Study of Nature Inspired Algorithms
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2017 by IJCTT Journal | ||
| Volume-49 Number-2 |
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| Year of Publication : 2017 | ||
| Authors : SanehLata Yadav, Manu Phogat | ||
| DOI : 10.14445/22312803/IJCTT-V49P115 |
SanehLata Yadav, Manu Phogat "Study of Nature Inspired Algorithms". International Journal of Computer Trends and Technology (IJCTT) V49(2):100-105, July 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Solving optimization problems becomes a central theme not only on operational research but also on several research areas like robotic, medicine, economic, Data-Mining etc. The number of support decision problems that can be formalized as an optimization problem is growing rapidly. In the communities of optimization, computational intelligence, and computer science, bio-inspired algorithms, especially those SI-based algorithms, have become very popular. In fact, these nature-inspired metaheuristic algorithms are now among the most widely used algorithms for optimization and computational intelligence. This survey discusses the various nature inspired meta-heuristic algorithms, and analyses the key components of these algorithms in terms of three evolutionary operators: crossover, mutation and selection.
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Keywords
Artificial Bee Colony, Ant Colony Optimization, Bat Algorithm, Cuckoo Search Algorithm.