Name
Abstract | ||
|---|---|---|
This paper studies the performance of a newly developed optimization algorithm inspired by the behavior of bison herds: the Bison Algorithm. The algorithm divides its population into two groups. The exploiting group simulates the swarming behavior of bison herds endangered by predators. The exploring group systematically runs through the search space in order to avoid local optima. At the beginning of the paper, the Bison Algorithm is introduced. Then the performance of the algorithm is compared to the Particle Swarm Optimization and the Cuckoo Search on the set of 30 benchmark functions of IEEE CEC 2017. Finally, the outcome of the experiments is discussed. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-91189-2_44 | ARTIFICIAL INTELLIGENCE AND ALGORITHMS IN INTELLIGENT SYSTEMS |
Keywords | Field | DocType |
Bison Algorithm,Bison,Optimization,Swarm algorithms,Metaheuristic | Population,Swarm algorithms,Endangered species,Computer science,Local optimum,Swarming (honey bee),Algorithm,Optimization algorithm,Metaheuristic | Conference |
Volume | ISSN | Citations |
764 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anezka Kazikova | 1 | 0 | 1.69 |
| Michal Pluhacek | 2 | 217 | 47.34 |
| Roman Senkerik | 3 | 375 | 74.92 |