Survey of Finding Solution for optimization problem using Ant Colony Optimization
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 142

India | Computer Science Engineering | Volume 4 Issue 10, October 2015 | Pages: 61 - 63


Survey of Finding Solution for optimization problem using Ant Colony Optimization

B. Sasikala, Dr. V. P. Eswaramurthy

Abstract: Ant Colony Optimization is one of the meta- heuristic algorithms and first member of ACO is Ant System (AS). AS uses a population of co-operating ants also known as agents. The cooperation phenomenon among the ants is called foraging and recruiting behavior. This describes how ants explore the world in search of food sources, then find their way back to the nest and indicate the food source to the other ants of the colony. The nature of ants, that collectively solve hard problems, gave rise to artificial ant algorithms. These algorithms were also proposed as a multi-agent approach in order to solve hard combinatorial optimization problems. ACO meta-heuristic introduces main features of artificial and these features have inspired different ant algorithms to solve hard optimization problems.

Keywords: Ant Colony Optimization ACO, meta-heuristic, Combinatorial Optimization Problem COP



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