HABCO: A robust agent on hybrid ant-bee colony optimization

Abba Suganda Girsang, Chun Wei Tsai, Chu-Sing Yang

Research output: Contribution to journalArticlepeer-review


The purpose of this research is to generate a robust agent by combining bee colony optimization (BCO) and ELU-Ants for solving traveling salesman problem (TSP), called HABCO. The robust agents, called ant-bees, firstly are grouped into three types scout, follower, recruiter at each stages. Then, the bad agents are high probably discarded, while the good agents are high probably duplicated in earlier steps. This first two steps mimic BCO algorithm. However, constructing tours such as choosing nodes, and updating pheromone are built by ELU-Ants 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.

Original languageEnglish
Pages (from-to)1247-1256
Number of pages10
JournalTelkomnika (Telecommunication Computing Electronics and Control)
Issue number3
Publication statusPublished - 2017 Sep 1

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'HABCO: A robust agent on hybrid ant-bee colony optimization'. Together they form a unique fingerprint.

Cite this