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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chun-Wei Tsai Kai-Cheng Hu Ming-Chao Chiang Chu-Sing Yang |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Electrical, Engineering, National Cheng Kung, University Tainan, Taiwan, R.O.C. (Chu-Sing Yang) || Department of Applied, Geoinformatics Chia Nan University of Pharmacy & Science Tainan, Taiwan, R.O.C. (Chun-Wei Tsai) || Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, R.O.C. (Kai-Cheng Hu; Ming-Chao Chiang) |
| Abstract | This paper presents a novel pheromone update strategy for improving the clustering results of ant colony optimization (ACO). The proposed algorithm is motivated by the observation that most of the ACOs only keep track of the promising foraging information, which has the potential to lead to better solutions than all the other search directions in the pheromone table. This eventually makes the search converge to particular search directions in later iterations because the pheromone values on good routing paths will be reinforced. As such, the breadth of search (diversity) will be reduced, thus limiting the clustering results of ACO. The proposed algorithm adds a second pheromone table to ACO for recording the unpromising foraging information that is worse than all the other search directions and using a novel construction method to explore the new search directions. In other words, by leveraging the strengths of diversification and intensification, the proposed algorithm can find better solutions than traditional ACO. To evaluate the performance of the proposed algorithm, we use it to solve the data clustering problem. Our experimental results indicate that the proposed algorithm can significantly improve the quality of ant colony optimization. |
| Starting Page | 2916 |
| Ending Page | 2921 |
| File Size | 178774 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424473151 |
| ISSN | 10987584 |
| e-ISBN | 9781424473175 |
| e-ISBN | 9781424473168 |
| DOI | 10.1109/FUZZY.2011.6007567 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-27 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Clustering algorithms Ant colony optimization Algorithm design and analysis Partitioning algorithms Routing Simulation Genetic algorithms clustering ant colony optimization pheromone table |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Theoretical Computer Science Software |
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