International Journal of Computer and Communication Technology


Ant colony optimization (ACO) is a novel computational technique inspired by a foraging behavior of ants has been successfully applied for solving real world optimization problems. This behavioral pattern inspires artificial ants for the search of solutions to the various types of optimization problems. ACO is a probabilistic search approach founded on the idea of evolutionary process. In this paper, we present an overview of ant colony optimization and ACO variants up to now. we also summarize various types of applications. Finally we focus on some research efforts directed at receiving a dipper understanding of the ant colony optimization algorithms.





To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.