TY - GEN
T1 - Hybrid ant colony optimization using memetic algorithm for traveling salesman problem
AU - Duan, Haibin
AU - Yu, Xiufen
PY - 2007
Y1 - 2007
N2 - Ant colony optimization was originally presented under the inspiration during collective behavior study results on real ant system, and it has strong robustness and easy to combine with other methods in optimization. Although ant colony optimization for the heuristic solution of hard combinational optimization problems enjoy a rapidly growing popularity, but little research is conducted on the optimum configuration strategy for the adjustable parameters in the ant colony optimization, and the performance of ant colony optimization depends on the appropriate setting of parameters which requires both human experience and luck to some extend. Memetic algorithm is a population-based heuristic search approach which can be used to solve combinatorial optimization problem based on cultural evolution. Based on the introduction of these two meta-heuristic algorithms, a novel kind of adjustable parameters configuration strategy based on memetic algorithm is developed in this paper, and the feasibility and effectiveness of this approach are also verified through the famous Traveling Salesman Problem(TSP). This hybrid approach is also valid for other types of combinational optimization problems.
AB - Ant colony optimization was originally presented under the inspiration during collective behavior study results on real ant system, and it has strong robustness and easy to combine with other methods in optimization. Although ant colony optimization for the heuristic solution of hard combinational optimization problems enjoy a rapidly growing popularity, but little research is conducted on the optimum configuration strategy for the adjustable parameters in the ant colony optimization, and the performance of ant colony optimization depends on the appropriate setting of parameters which requires both human experience and luck to some extend. Memetic algorithm is a population-based heuristic search approach which can be used to solve combinatorial optimization problem based on cultural evolution. Based on the introduction of these two meta-heuristic algorithms, a novel kind of adjustable parameters configuration strategy based on memetic algorithm is developed in this paper, and the feasibility and effectiveness of this approach are also verified through the famous Traveling Salesman Problem(TSP). This hybrid approach is also valid for other types of combinational optimization problems.
UR - https://www.scopus.com/pages/publications/34548739807
U2 - 10.1109/ADPRL.2007.368174
DO - 10.1109/ADPRL.2007.368174
M3 - 会议稿件
AN - SCOPUS:34548739807
SN - 1424407060
SN - 9781424407064
T3 - Proceedings of the 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning, ADPRL 2007
SP - 92
EP - 95
BT - Proceedings of the 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning, ADPRL 2007
T2 - 2007 IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning, ADPRL 2007
Y2 - 1 April 2007 through 5 April 2007
ER -