Name
Title | ||
|---|---|---|
Multi-population techniques in nature inspired optimization algorithms: A comprehensive survey. |
Abstract | ||
|---|---|---|
Multi-population based nature-inspired optimization algorithms have attracted wide research interests in the last decade, and become one of the frequently used methods to handle real-world optimization problems. Considering the importance and value of multi-population methods and its applications, we believe it is the right time to provide a comprehensive survey of the published work, and also to discuss several aspects for the future research. The purpose of this paper is to summarize the published techniques related to the multi-population methods in nature-inspired optimization algorithms. Beginning with the concept of multi-population optimization, we review basic and important issues in the multi-population methods and discuss their applications in science and engineering. Finally, this paper presents several interesting open problems with future research directions for multi-population optimization methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.swevo.2018.04.011 | Swarm and Evolutionary Computation |
Keywords | Field | DocType |
Multi-population,Nature-inspired algorithm,Optimization,Evolutionary algorithm,Swarm intelligence | Population,Computer science,Optimization algorithm,Optimization problem,Management science | Journal |
Volume | ISSN | Citations |
44 | 2210-6502 | 10 |
PageRank | References | Authors |
0.44 | 105 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haiping Ma | 1 | 450 | 23.63 |
| Shigen Shen | 2 | 185 | 14.77 |
| Mei Yu | 3 | 13 | 2.92 |
| Zhile Yang | 4 | 71 | 14.83 |
| Minrui Fei | 5 | 1003 | 117.54 |
| Huiyu Zhou | 6 | 1303 | 111.91 |