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Chu-Sing Yang
National Cheng Kung University
Computer Science & IT

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HABCO: A Robust Agent on Hybrid Ant-Bee Colony Optimization Abba Suganda Girsang; Chun-Wei Tsai; Chu-Sing Yang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 3: September 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i3.3656

Abstract

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.
Co-Authors Abba Suganda Girsang, Abba Suganda Chun-Wei Tsai