Name
Abstract | ||
|---|---|---|
Artificial bee colony (ABC) is an efficient global optimisation algorithm. It has attracted the attention of many researchers because of its simple concept and strong exploration. However, it exhibits weak exploitation capability. To improve this case, a novel ABC with modified search strategy (namely MSABC) is proposed in this work. In MSABC, some modified elite solutions are preserved and used to guide the search. In addition, MSABC uses the modified elite solutions to generate offspring to replace the probability selection in the onlooker bee phase. To evaluate the capability of MSABC, 22 classical problems are tested. Results demonstrate MSABC achieves superior performance than five other ABC variants. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1504/IJCSM.2022.10050785 | INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS |
Keywords | DocType | Volume |
ABC, artificial bee colony, elite solution, search strategy, probability selection, modified search strategy, Euclidean distance, weak exploitation, strong exploration, global optimisation, function optimisation, optimisation | Journal | 15 |
Issue | ISSN | Citations |
4 | 1752-5055 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai Li | 1 | 2 | 4.49 |
| Minyang Xu | 2 | 0 | 1.01 |
| Tao Zeng | 3 | 0 | 0.34 |
| Tingyu Ye | 4 | 0 | 0.34 |
| Luqi Zhang | 5 | 0 | 0.34 |
| Wenjun Wang | 6 | 11 | 1.99 |
| Hui Wang | 7 | 291 | 85.17 |