Research And Application Of The Improved Ant Colony Algorithm

With the increase of complexion and scale in optimization,it is found more difficult to solve problems with single algorithm.The combination of algorithms shows its superiority in solving problems.This paper focuses on the algorithm of the model,the behavior,the characteristics and improvements,and raises a model of ACA on continuous space optimization problems.Then the convergence of the improvement algorithm is given. And a simulation is used for the purpose of verifying the validity of the model.Firstly,the biological mechanism,the development and the character of the ant colony algorithm are outlined,and the current situations of research and application of the ant colony algorithm are introduced.Then the principle,the model,the characteristics and the management about the basic algorithm of ACO are also presented.Moreover,a list of improvements is also introduced.In addition,the basic idea of Artificial Fish Swarm Algorithm(AFSA),characteristics and research situation are briefly discussed.Secondly,for the shortages of ACO,an improvement which is taking use of the characteristics of AFSA is presented.Simulation results show the feasibility and validity of the improvement algorithm,and the convergence of the improvement algorithm is given.Thirdly,ACO is taken into image matching,and the simulation shows the feasibility of the algorithm.Finally,it summarizes the work of the paper and discusses the related problems in the future.