Examining the Solution for Solving Optimization Problems using Swarm Intelligence and Its Applications

SI is a computational and collective behavioral metaphor that is used for solving problems. The problems can be solved by SI by taking ants, termites, bees and wasps as an example. The application of SI algorithm are ACO, PSO and ABC which have been already applied to solve real world optimization problems in engineering. ACO is a member of SI in which ACO is inspired by the behaviour of ant colonies and it constitutes some metaheuristic optimization. ACO’s aim is to search for an optimal path with the help of graph. In PSO, a solution of continuous optimization problems can be solved , because PSO is population based stochastic optimization techniques for the solution of continuous optimization problem. In ABC the solution for the problem is found with help of foraging behaviour of honey bees. It is also swarm based meta heuristic algorithm. This paper presents the experimental verification of ACO and EACO.