Improved ant colony algorithm based on membership cloud models

To overcome the slow convergence and local extrema of ant colony algorithm(ACA),improvements are proposed in this article.Firstly,control the randomness of the ants via cloud model;secondly,reduce the search region of subsequent cities.Finally, introduce the 2-opt local search strategy.Simulations are implemented on various TSP with cities from 50 to 1 000,and this pro-posed algorithm is compared with old algorithm.Results demonstrate that the gap of this proposed algorithm is lower and the com-putation time is shorter than old methods,the advantages becoming notable with the number of cities becoming larger.