Name
Title | ||
|---|---|---|
Opposition-based Learning Harris Hawks Optimization with Advanced Transition Rules: Principles and Analysis |
Abstract | ||
|---|---|---|
•A new method to solve global optimization and engineering problems called m-HHO.•The m-HHO improves the HHO using new transition rule and opposition-based learning.•A collection of 33 benchmarks is taken to evaluate the performance.•The m-HHO is also tested on engineering optimization problems.•Comparisons illustrate the improvement on the performance of m-HHO. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2020.113510 | Expert Systems with Applications |
Keywords | DocType | Volume |
Meta-heuristics,Harris hawks optimizer,Exploration and exploitation,Nature-inspired algorithms | Journal | 158 |
ISSN | Citations | PageRank |
0957-4174 | 11 | 0.43 |
References | Authors | |
36 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shubham Gupta | 1 | 278 | 27.57 |
| Kusum Deep | 2 | 876 | 82.14 |
| Ali Asghar Heidari | 3 | 439 | 17.20 |
| Hossein Moayedi | 4 | 176 | 18.49 |
| Mingjing Wang | 5 | 11 | 0.43 |