Improvements of ant colony algorithm and its applications in artificial neural network

Kuangfeng Ning, Xiliang Zeng

Hunan University of International Economics, Changsha 410205, Hunan, China

Ant colony algorithm (ACA) is a bionic intelligent optimization algorithm with positive feedback, distributed computing and heuristic search. As an important branch of computational intelligence and swarm intelligence, ACA has been successfully applied in solving many combinatorial optimization problems. Artificial neural network is a large-scale distributed parallel processing system with the characteristics of self-organization, self-study, self-adaptation and non-linear dynamic processing and it has a broad prospect in settling the complicated non-linear problems. This paper has proposed an algorithm used to solve multi-objective optimization problems and the applications of ACA.