Name
Title | ||
|---|---|---|
Hybridizing Shuffled Frog Leaping and Shuffled Complex Evolution Algorithms Using Local Search Methods |
Abstract | ||
|---|---|---|
In this research, a study was carried out to exploit the hybrid schemes combining two classical local search techniques i.e. Nelder-Mead simplex search method and bidirectional random optimization with two meta-heuristic methods i.e. the shuffled frog leaping and the shuffled complex evolution, respectively. In this hybrid methodology, each subset of meta-heuristic algorithms is improved by a hybrid strategy that is combined from evolutionary process of each subset in related algorithm and a local search method. These hybrid algorithms are evaluated on low and high dimensional continuous benchmark functions and the obtained results are compared with their non-hybrid competitors. The obtained results demonstrate that the hybrid algorithm combined from shuffled frog leaping and Nelder-Mead simplex has a better success rate but a higher number of function evaluations on low-dimensional functions than the shuffled frog leaping. Whereas on high-dimensional functions it has a better success rate and a faster performance. Also the hybrid algorithm combined from shuffled complex evolution and bidirectional random optimization obtains a better performance in terms of success rate and function evaluations than shuffled complex evolution on low dimensional functions; whereas on high-dimensional functions, it obtains a better success rate but a slower performance. Also a comparison of our hybrid algorithms with the other evolutionary algorithms reported in the literature confirms our proposed algorithms have the best performance among all compared algorithms. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.4018/ijaec.2014010103 | International Journal of Applied Evolutionary Computation |
Keywords | Field | DocType |
bidirectional random optimization,nelder-mead simplex search,hybrid algorithms,shuffled frog leaping,shuffled complex evolution | Mathematical optimization,Hybrid algorithm,Evolutionary algorithm,Computer science,Algorithm,Simplex,Artificial intelligence,Local search (optimization),Random optimization,Machine learning | Journal |
Volume | Issue | Citations |
5 | 1 | 0 |
PageRank | References | Authors |
0.34 | 17 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Morteza Alinia Ahandani | 1 | 76 | 6.71 |
| Hosein Alavi-Rad | 2 | 41 | 3.52 |