|International Journal of Computer Applications
|Foundation of Computer Science (FCS), NY, USA
|Volume 38 - Number 6
|Year of Publication: 2012
|Authors: S.Padmanabhan, Dr.M.Chandrasekaran, Dr. V.Srinivasa Raman
S.Padmanabhan, Dr.M.Chandrasekaran, Dr. V.Srinivasa Raman . Evaluation of the Performance of Ant Colony Optimization over Particle Swarm Optimization. International Journal of Computer Applications. 38, 6 ( January 2012), 12-18. DOI=10.5120/4691-6826
Traditional mathematical algorithms are incapable of solving real time engineering design problems because of its rigid procedure mainly due to discrete or random data and multi-objective functions in a problem. An optimization algorithm is a procedure which is executed iteratively by comparing various solutions till the optimum or a satisfactory solution is found. There are two population based Swarm inspired methods in computational intelligence areas: Ant colony optimization (ACO) and Particle swarm optimization (PSO). This paper made an attempt to evaluate their performance of these two swarm intelligence techniques. A real engineering application of bevel gear design optimization is considered and results are analyzed with respect to the context.