Abstract: Aimed at the defects such as slow convergence and easy to fall into local optimization for standard ant colony algorithm to solve traveling salesman problem(TSP). Combinatorial optimization problem is transformed to searching farina for honey bees, based on the analysis of nectar searching, and artificial bee colony algorithm with three basic models is analyzed. Three regenerative strategies of leading gene are discussed. Dynamic renew formula of transforming gene and transferring formula of state are established and honeybee algorithm model. At last, concrete process of solving TSP by adopting ABC is proposed and some typical TSP samples are practiced. The results show that this algorithm can avoid pre-maturity and advance constringency and the algorithm has more advantages than ant standard colony algorithm.