A Study on the Performance of Grey Wolf Optimizer
| dc.contributor.author | Çiftçioğlu A.Ö. | |
| dc.date.accessioned | 2024-07-22T08:06:23Z | |
| dc.date.available | 2024-07-22T08:06:23Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | In recent years there is an enormous increase in the emergence of non-deterministic search methods. The effective way of animals in problem-solving (like discovering the shortest path to the food source) has been examined by scientists and swarm intelligence has become a research field that imitates the behaviour of animals in swarm. The moth-flame optimization (MFO) algorithm, salp swarm algorithm (SSA), firefly algorithm (FFA), bat (BAT) algorithm, cuckoo search (CS) algorithm, genetic algorithm (GA), and grey wolf optimizer (GWO) are some of the swarm intelligence based non-deterministic methods. In the present study, the seven methods above are investigated separately. Five mathematical functions are resolved individually by these seven methods. Each algorithm is run 30 times in each benchmark function. The performances of these optimization methods are evaluated and compared within each function individually. Performances of algorithms over convergence are compared by plotting convergence rate graph and boxplots of methods for each function. Considering most of the functions, GWO is observed to be stronger than other algorithms. © 2021, Springer Nature Switzerland AG. | |
| dc.identifier.DOI-ID | 10.1007/978-3-030-89743-7_7 | |
| dc.identifier.issn | 18650929 | |
| dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/13488 | |
| dc.language.iso | English | |
| dc.publisher | Springer Science and Business Media Deutschland GmbH | |
| dc.subject | Functions | |
| dc.subject | Genetic algorithms | |
| dc.subject | Problem solving | |
| dc.subject | Stochastic systems | |
| dc.subject | Swarm intelligence | |
| dc.subject | Comparison | |
| dc.subject | Deterministics | |
| dc.subject | Gray wolves | |
| dc.subject | Optimisations | |
| dc.subject | Optimizers | |
| dc.subject | Performance | |
| dc.subject | Problem-solving | |
| dc.subject | Search method | |
| dc.subject | Short-path | |
| dc.subject | Stochastic search methods | |
| dc.subject | Animals | |
| dc.title | A Study on the Performance of Grey Wolf Optimizer | |
| dc.type | Conference paper |