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| Lifecycle-Based Binary Ant Colony Optimization Algorithm |
| CHENG Mei-Ying, NI Zhi-Wei, ZHU Xu-Hui |
1School of Management, Hefei University of Technology,Hefei 230009
2Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education,
Hefei University of Technology, Hefei 230009 |
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Abstract The biological life cycle in natural ecosystem is introduced into binary ant colony optimization algorithm, and the main idea is to execute breeding, migrating and dying operations by setting relevant nutritious threshold value to the ants. Thus, the dynamic diversity of the population is maintained and the drawback that binary ant colony optimization algorithm easily traps in local optimum is overcome. The proposed algorithm, lifecycle-based binary ant colony optimization algorithm (LCBBACO), is combined with fractal dimension to attribute reduction problem. The experimental results on 6 UCI datasets show that the method has preferable feasibility and effectiveness.
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Received: 20 January 2014
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2014, Vol. 27 
