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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiong Hui Xiu Chunbo |
| Copyright Year | 2009 |
| Abstract | A new ant colony optimization algorithm is proposed to resolve combinatorial optimization problem. The performance of the optimization algorithm can be improved by the chaos annealing. In the incipient optimization process, ants search the new path not only according to the concentration of the pheromone, but also the chaos guidance, which make the algorithm have the stronger ergodicity searching ability. In the terminal optimization process, the chaos decayed to zero gradually. In the end, the algorithm transforms into the conventional ant colony algorithm and completes the optimal process by the principle of pheromone positive feedback, which insures the algorithm to have a quick convergence rate. The simulation results prove the validity of the algorithm. |
| Starting Page | 176 |
| Ending Page | 178 |
| File Size | 236673 |
| Page Count | 3 |
| File Format | |
| ISBN | 9780769539300 |
| e-ISBN | 9781424454235 |
| DOI | 10.1109/IFCSTA.2009.50 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-12-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Chaos Ant colony optimization Annealing Chaotic communication Feedback Computer applications Traveling salesman problems Cities and towns Ant colony Application software Combinatorial optimization Convergence |
| Content Type | Text |
| Resource Type | Article |
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