Name
Title | ||
|---|---|---|
Extremely high-dimensional optimization with MapReduce: Scaling functions and algorithm. |
Abstract | ||
|---|---|---|
•We present a MapReduce implementation of the MA-SW-Chains algorithm.•MapReduce allows the scalability of the benchmark functions to millions of variables.•A coevolutionary fasion of the Subgrouping Solis Wets improves local search.•Results are provided on 10 million dimensions for the first time on CEC functions. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.ins.2017.06.024 | Information Sciences |
Keywords | Field | DocType |
Real optimization,High-dimensional optimization,MapReduce | Continuous optimization,Memetic algorithm,Computer science,Algorithm,Curse of dimensionality,Parallel programming model,Heuristics,Artificial intelligence,Scaling,Optimization problem,Computer cluster,Machine learning | Journal |
Volume | ISSN | Citations |
415 | 0020-0255 | 6 |
PageRank | References | Authors |
0.39 | 36 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto Cano | 1 | 130 | 11.20 |
| Carlos GarcíA-MartíNez | 2 | 520 | 27.80 |
| S. Ventura | 3 | 2318 | 158.44 |