This paper research review Ant colony optimization (ACO) and Genetic Algorithm (GA), both are two powerful meta-heuristics. This paper explains some major defects of these two algorithm at first then proposes a new model for ACO in which, artificial ants use a quick genetic operator and accelerate their actions in selecting next state. Experimental results show that proposed hybrid algorithm is effective and its performance including speed and accuracy beats other version.
@article{arxiv.1411.2897,
title = {Accelerating the ANT Colony Optimization By Smart ANTs, Using Genetic Operator},
author = {Hassan Ismkhan},
journal= {arXiv preprint arXiv:1411.2897},
year = {2014}
}
Comments
International Journal on Computational Science & Applications, Volume: 4 - volume NO: 2 - Issue: April 2014