Ant Colony System Algorithm Based On Extension

The ant colony optimization (ACO) is a relatively new meta-heuristic algorithm and a successful paradigm of all the algorithms which take advantage of the insects' behavior. The ACO solves problems through mimicking ants' foraging behavior. Essentially, the ACO is a parallel and self-organizing algorithm, which can be applied to improve the management and control of large numbers of interacting entities. The objects of the extencis are contradictory problems in the realistic world, and the research direction discuss methods of dealing with contradictory problems. In the research technique, there are some differences from social sciences and extencis, which try to formalize the process when people settle contradiction problem and establish the extension model in the same time. Based on this, some new method of design and technique of engineering are produced.This article presents the basic thinking, theoretical system, the origin andenrichment of the ACO, summarizes this algorithm's advantages, disadvantages, and hybridizing other optimization algorithm. A new algorithm combining ant colony system with extension is proposed to overcome these disadvantages, After discussing several problems existing in the research, this article puts forward the research foreground of ant colony system algorithm based on extension.