An Improved Genetic & Ant Colony Optimization Algorithm for Travelling Salesman Problem

Ant Colony Algorithm (ACA) and Generation Algorithm (GA) are two bionic optimization algorithm, they are also two powerful and effective algorithms for solving the combination optimization problems, moreover they all were successfully used in traveling salesman problem (TSP) . This paper syncretizes two algorithms, meanwhile, a new syncretic method is put forward. The simulation results show that the new algorithm of ACA and GA is better at improving global convergence and quickening the speed of convergence.