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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xianjun Shen Kaiping Wei Deming Wu Yala Tong Yuanxiang Li |
| Copyright Year | 2007 |
| Description | Author affiliation: Central China Normal Univ., Wuhan (Xianjun Shen; Kaiping Wei) |
| Abstract | An adaptive dissipative particle swarm with mutation operation (ADPSO) is presented that combines the idea of the particle swarm optimization with concepts of mutation from evolutionary algorithm. In this paper, the problem and improved of the dissipative particle swarm optimization are analyzed deeply. The improvement ADPSO adopts Cauchy mutation operation to escape from the attraction of local minimum. In order to balance between global and local search, the adaptive inertia weight strategy is introduced. The simulation experiments demonstrate that ADPSO can not only effectively escape from local minimum, but also enhance the capability to search the global optimization in the later convergence phase. |
| Starting Page | 586 |
| Ending Page | 589 |
| File Size | 307187 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424408177 |
| DOI | 10.1109/ICCA.2007.4376423 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-05-30 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Particle swarm optimization Genetic mutations Evolutionary computation Programmable control Adaptive control Convergence Equations Centralized control Automatic control Automation global optimization adaptive dissipative particle swarm Cauchy mutation |
| Content Type | Text |
| Resource Type | Article |
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