TY - GEN
T1 - A hybrid ant-bee colony optimization for solving traveling salesman problem with competitive agents
AU - Girsang, Abba Suganda
AU - Tsai, Chun Wei
AU - Yang, Chu Sing
PY - 2014/1/1
Y1 - 2014/1/1
N2 - This paper presents a new method called hybrid ant bee colony optimization (HABCO) for solving traveling salesman problem which combines ant colony system (ACS), bee colony optimization (BCO) and ELU-Ants. The agents, called ant-bees, are grouped into three types, scout, follower, recruiter at each stages as BCO algorithm. However, constructing tours such as choosing nodes, and updating pheromone are built by ACS method. To evaluate the performance of the proposed algorithm, HABCO is performed on several benchmark datasets and compared to ACS and BCO. The experimental results show that HABCO achieves the better solution, either with or without 2opt.
AB - This paper presents a new method called hybrid ant bee colony optimization (HABCO) for solving traveling salesman problem which combines ant colony system (ACS), bee colony optimization (BCO) and ELU-Ants. The agents, called ant-bees, are grouped into three types, scout, follower, recruiter at each stages as BCO algorithm. However, constructing tours such as choosing nodes, and updating pheromone are built by ACS method. To evaluate the performance of the proposed algorithm, HABCO is performed on several benchmark datasets and compared to ACS and BCO. The experimental results show that HABCO achieves the better solution, either with or without 2opt.
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U2 - 10.1007/978-3-642-40675-1_95
DO - 10.1007/978-3-642-40675-1_95
M3 - Conference contribution
AN - SCOPUS:84958546651
SN - 9783642406744
T3 - Lecture Notes in Electrical Engineering
SP - 643
EP - 648
BT - Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013
PB - Springer Verlag
T2 - 4th International Conference on Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013
Y2 - 4 September 2013 through 6 September 2013
ER -