Name
Title | ||
|---|---|---|
DCDG-EA: Dynamic convergence-diversity guided evolutionary algorithm for many-objective optimization. |
Abstract | ||
|---|---|---|
•DCDG-EA algorithm uses reference vector decomposition to solve MaOPs.•CDOS selects an appropriate operator to generate offspring.•CDIS strategy simultaneously considers the convergence and diversity of solutions. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2018.09.025 | Expert Systems with Applications |
Keywords | Field | DocType |
Many-objective optimization,Convergence,Diversity,Decomposition,Evolutionary algorithm,Pareto optimality | Convergence (routing),Mathematical optimization,Subspace topology,Evolutionary algorithm,Computer science,Linear subspace,Operator (computer programming),Artificial intelligence,Optimization problem,Pareto principle,Machine learning,Distance measures | Journal |
Volume | ISSN | Citations |
118 | 0957-4174 | 1 |
PageRank | References | Authors |
0.36 | 29 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiyong Li | 1 | 64 | 11.15 |
| Ke Lin | 2 | 1 | 0.36 |
| Mourad Nouioua | 3 | 5 | 2.10 |
| Shilong Jiang | 4 | 3 | 2.10 |
| Yu Gu | 5 | 28 | 7.96 |