Name
Abstract | ||
|---|---|---|
An adaptive gradient multiobjective particle swarm optimization (AGMOPSO) algorithm, based on a multiobjective gradient (stocktickerMOG) method and a self-adaptive flight parameters mechanism, is developed to improve the computation performance in this paper. In this AGMOPSO algorithm, the stocktickerMOG method is devised to update the archive to improve the convergence speed and the local exploit... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCYB.2017.2756874 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Convergence,Optimization,Algorithm design and analysis,Particle swarm optimization,Heuristic algorithms,Clustering algorithms,Cybernetics | Particle swarm optimization,Convergence (routing),Mathematical optimization,Algorithm design,Multi-swarm optimization,Artificial intelligence,Cluster analysis,Cybernetics,Mathematics,Machine learning,Metaheuristic,Computation | Journal |
Volume | Issue | ISSN |
48 | 11 | 2168-2267 |
Citations | PageRank | References |
4 | 0.39 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong-Gui Han | 1 | 476 | 39.06 |
| 卢薇 | 2 | 4 | 0.39 |
| 张璐 | 3 | 7 | 0.81 |
| 乔俊飞 | 4 | 44 | 2.77 |
| Honggui Han | 5 | 4 | 0.39 |
| Wei Lu | 6 | 319 | 62.97 |
| Lu Zhang | 7 | 163 | 40.09 |
| Junfei Qiao | 8 | 4 | 0.39 |