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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yongjing Chen Zhihua Cui Jianchao Zeng |
| Copyright Year | 2010 |
| Description | Author affiliation: Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Taiyuan, Shanxi, PR. China (Yongjing Chen; Zhihua Cui; Jianchao Zeng) |
| Abstract | Structural optimization of Lennard-Jones (LJ) clusters is a classical NP problem. There are many local minima locating near the global minimum, and the local optima number is increased exponentially. Social cognitive optimization. algorithm (SCOA) is a new swarm intelligent technique by simulating the human society. However, its local search capability is still weak. Therefore, in this paper, a novel local search strategy, Limited memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) is employed to enhance the exploitation capability of SCOA. Simulation results show the proposed hybrid algorithm has successfully found the lowest-energy structures of the LJ2-LJ5, LJ7-LJ9 and LJ12 comparing with PSO and the standard SCOA. |
| Starting Page | 204 |
| Ending Page | 208 |
| File Size | 248420 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424480418 |
| e-ISBN | 9781424480425 |
| DOI | 10.1109/COGINF.2010.5599739 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Optimization Clustering algorithms Indexes Particle swarm optimization Humans Electronic mail Simulation Lennard-Jones(LJ) Clusters SCOA L-BFGS |
| Content Type | Text |
| Resource Type | Article |
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