A self-adaptive Ant Algorithm with changing index

The purpose of this paper is to propose an improved algorithm to overcome the premature deficiency of the basic ant algorithm, which is a novel simulated evolutionary algorithm, also a newly stochastic and intellectual searching optimization. After systematically analyzing the basic knowledge of the basic ant algorithm-ant system algorithm, an improved ant algorithm with a strategy of changing index self-adaptively which based on information is proposed. The information entropy was introduced to measure the uncertainty of the selection which is related to the parameter of the algorithm. Then, the improved algorithm was introduced into the traveling salesman problem and its ability for optimizing is discussed. This study provides an effective method for solving the premature problem of the similar algorithms.