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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shan Cheng Gang Hu Tian-Ya Qin |
| Copyright Year | 2014 |
| Description | Author affiliation: Coll. of Electr. Eng. & New Energy, China Three Gorges Univ., Yichang, China (Shan Cheng; Tian-Ya Qin) || Sch. of Electr. & Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China (Gang Hu) |
| Abstract | One of the most important features of the PSO algorithm is its fast convergence. This is a positive feature as long as there's no premature convergence. Inspired by the phenomenon of quorum sensing behavior in the bacteria, we incorporate this bio-behavior into PSO and MOPSO to maintain the swarm diversity and promote global exploration when the velocity of each particle in the swarm is rather small. The effectiveness of applying quorum sensing to PSO and MOPSO has been tested on a set of benchmark functions and compared with representative algorithms. Simulation results illustrate that application of quorum sensing to PSO and MOPSO enables to promote their convergence, the proposed algorithms with introduction of quorum sensing mechanism are rather competitive and could be used as effective global optimization tools. |
| Starting Page | 1106 |
| Ending Page | 1110 |
| File Size | 243309 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479937073 |
| e-ISBN | 9781479937080 |
| DOI | 10.1109/CCDC.2014.6852330 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-05-31 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Multi-objective particle swarm optimization Microorganisms Premature convergence Sociology Benchmark testing Quorum sensing Sensors Particle swarm optimization Statistics Convergence |
| Content Type | Text |
| Resource Type | Article |
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