%0 Journal Article %A CHEN Lei %A ZHANG Hongmei %A ZHANG Xiangli %T Adaptive dynamic neighborhood hybrid cuckoo search algorithm for solving traveling salesman problems %D 2018 %R 10.3778/j.issn.1002-8331.1712-0281 %J Computer Engineering and Applications %P 42-50 %V 54 %N 23 %X In view of the deficiencies of discrete cuckoo search algorithm for solving Traveling Salesman Problem(TSP) like easy to fall into the local optimal solution and low efficiency of local search. An adaptive dynamic neighborhood hybrid cuckoo search algorithm is proposed. To improve the local search efficiency, a circle-restricted dynamic neighborhood structure is designed to reduce the randomness. In addition, the strategy of adaptive parameter adjustment based on the iterative process is proposed, and the tabu search algorithm is used to improve the ability of searching global optimum solution. Finally, using MATLAB and some instances in TSPLIB database to test the performance of the algorithm, the results show that compared with other cuckoo search algorithms, new intelligence algorithms and classical intelligent optimization algorithms, ADNHCS algorithm has better performance in global optimization and stability. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1712-0281