Cluster Integrated Updation Strategies for ACO Algorithms

Cluster Integrated Updation Strategies for ACO Algorithms

Cluster Integrated Updation Strategies for ACO Algorithms

Ant Colony Optimization (ACO) algorithm has evolved as the most popular way to attack the combinatorial problems. The ACO algorithm employs multi agents called ants that are capable of finding optimal solution for a given problem instances. These ants at each step of the computation make probabilistic choices to include good solution component in partially 1 / 4

Unsupervised Updation Strategies for ACO Algorithms

Ant Colony Optimization (ACO) algorithms belong to class of metaheuristic algorithms, where a search is made for optimized solution rather than exact solution, based on the knowledge of the problem domain. ACO algorithms are iterative in nature. As the iteration proceeds, solution converges to the optimized solution. In this paper, we propose new updation mechanism based on clustering technique...

Unsupervised Updation Strategies for ACO Algorithms

Ant Colony Optimization (ACO) algorithms belong to class of metaheuristic algorithms, where a search is made for optimized solution rather than exact solution, based on the knowledge of the problem domain. ACO algorithms are iterative in nature. As the iteration proceeds, solution converges to the optimized solution. In this paper, we propose new updation mechanism based 1 / 4

Unsupervised Updation Strategies for ACO Algorithms