Name
Abstract | ||
|---|---|---|
In this paper, we introduce a new dynamical evolutionary algorithm (DEA) that aims to find the global optimum and give the theoretical explanation from statistical mechanics. The algorithm has been evaluated numerically using a wide set of test functions which are nonlinear, multimodal and multidimensional. The numerical results show that it is possible to obtain global optimum or more accurate solutions than other methods for the investigated hard problems. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1080/0020716031000148485 | INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS |
Keywords | Field | DocType |
dynamical evolutionary algorithm, statistical mechanics, global optimization, genetic algorithm | Mathematical optimization,Statistical mechanics,Nonlinear system,Evolutionary algorithm,Global optimization,Global optimum,Numerical analysis,Genetic algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
80 | 11 | 0020-7160 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiufen Zou | 1 | 272 | 25.44 |
| Yuanxiang Li | 2 | 245 | 51.20 |
| Lishan Kang | 3 | 775 | 91.11 |
| Zhijian Wu | 4 | 247 | 18.55 |