Name
Abstract | ||
|---|---|---|
•Heap-based optimizer (HBO) inspired by corporate rank hierarchy (CRH) is proposed.•HBO utilizes heap to map the hierarchy and model equations for 3 CRH activities.•A parameter (γ) to escape local optima without lacking exploitation is introduced.•Exploration and exploitation are balanced through self-adaptive parameters.•Performance is evaluated on 97 benchmarks and 3 mechanical engineering problems. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2020.113702 | Expert Systems with Applications |
Keywords | DocType | Volume |
Social optimization algorithm,Corporate hierarchy based optimization,Nature-inspired meta-heuristic,Global optimization algorithm | Journal | 161 |
ISSN | Citations | PageRank |
0957-4174 | 11 | 0.48 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qamar Askari | 1 | 23 | 2.35 |
| Mehreen Saeed | 2 | 87 | 7.32 |
| Irfan Younas | 3 | 26 | 4.72 |