[PDF][PDF] Swarm intelligence from natural to artificial systems: Ant colony optimization

O Deepa, A Senthilkumar - Networks (Graph-Hoc), 2016 - academia.edu
O Deepa, A Senthilkumar
Networks (Graph-Hoc), 2016academia.edu
Successful applications coming from biologically inspired algorithm like Ant Colony
Optimization (ACO) based on artificial swarm intelligence which is inspired by the collective
behavior of social insects. ACO has been inspired from natural ants system, their behavior,
team coordination, synchronization for the searching of optimal solution and also maintains
information of each ant. At present, ACO has emerged as a leading metaheuristic technique
for the solution of combinatorial optimization problems which can be used to find shortest …
Abstract
Successful applications coming from biologically inspired algorithm like Ant Colony Optimization (ACO) based on artificial swarm intelligence which is inspired by the collective behavior of social insects. ACO has been inspired from natural ants system, their behavior, team coordination, synchronization for the searching of optimal solution and also maintains information of each ant. At present, ACO has emerged as a leading metaheuristic technique for the solution of combinatorial optimization problems which can be used to find shortest path through construction graph. This paper describe about various behavior of ants, successfully used ACO algorithms, applications and current trends. In recent years, some researchers have also focused on the application of ACO algorithms to design of wireless communication network, bioinformatics problem, dynamic problem and multi-objective problem.
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