Numerical Simulation Analysis and Research of Improved Ant Colony Algorithm Based on Comentropy

Ant colony algorithm (ACA) is a heuristic search algorithm to solve combinational optimization problems whose selection strategy has direct relations with the information content of the routes which is indefinite. Based on comparison of several improved algorithms, improved ACA based on comentropy is proposed in the paper. By controlling comentropy figure, route selection and the probability of local random mutation perturbation can be controlled to achieve adaptive adjustment. The superiority of the improved algorithm is proved by experimental data.