TY - GEN
T1 - A multi-objective ant colony optimization algorithm based on the physarum-inspired mathematical model
AU - Liu, Yuxin
AU - Lu, Yuxiao
AU - Gao, Chao
AU - Zhang, Zili
AU - Tao, Li
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - Multi-objective traveling salesman problem (MOTSP) is an important field in operations research, which has wide applications in the real world. Multi-objective ant colony optimization (MOACO) as one of the most effective algorithms has gained popularity for solving a MOTSP. However, there exists the problem of premature convergence in most of MOACO algorithms. With this observation in mind, an improved multiobjective network ant colony optimization, denoted as PMMONACO, is proposed, which employs the unique feature of critical tubes reserved in the network evolution process of the Physarum-inspired mathematical model (PMM). By considering both pheromones deposited by ants and flowing in the Physarum network, PM-MONACO uses an optimized pheromone matrix updating strategy. Experimental results in benchmark networks show that PM-MONACO can achieve a better compromise solution than the original MOACO algorithm for solving MOTSPs.
AB - Multi-objective traveling salesman problem (MOTSP) is an important field in operations research, which has wide applications in the real world. Multi-objective ant colony optimization (MOACO) as one of the most effective algorithms has gained popularity for solving a MOTSP. However, there exists the problem of premature convergence in most of MOACO algorithms. With this observation in mind, an improved multiobjective network ant colony optimization, denoted as PMMONACO, is proposed, which employs the unique feature of critical tubes reserved in the network evolution process of the Physarum-inspired mathematical model (PMM). By considering both pheromones deposited by ants and flowing in the Physarum network, PM-MONACO uses an optimized pheromone matrix updating strategy. Experimental results in benchmark networks show that PM-MONACO can achieve a better compromise solution than the original MOACO algorithm for solving MOTSPs.
KW - Multi-objective ant colony optimization algorithms
KW - Multi-objective traveling salesman problem
KW - Physarum-inspired mathematical model
UR - http://www.scopus.com/inward/record.url?scp=84926642538&partnerID=8YFLogxK
U2 - 10.1109/ICNC.2014.6975852
DO - 10.1109/ICNC.2014.6975852
M3 - 会议稿件
AN - SCOPUS:84926642538
T3 - 2014 10th International Conference on Natural Computation, ICNC 2014
SP - 303
EP - 308
BT - 2014 10th International Conference on Natural Computation, ICNC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 10th International Conference on Natural Computation, ICNC 2014
Y2 - 19 August 2014 through 21 August 2014
ER -