Name
Abstract | ||
|---|---|---|
This paper proposes a simple, yet effective, modification to scaling factor and crossover rate adaptation in Success-History based Adaptive Differential Evolution (SHADE), which can be used as a framework to all SHADE-based algorithms. The performance impact of the proposed method is shown on the CEC2015 benchmark set in 10 and 30 dimensions for both SHADE and L-SHADE (SHADE with linear decrease of population size) algorithms. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/SSCI.2017.8280959 | 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) |
Keywords | Field | DocType |
differential evolution, shade, l-shade, parameter adaptation, scaling factor, crossover rate | Convergence (routing),Scale factor,Mathematical optimization,Differential evolution,Population size,Linear programming,Crossover rate | Conference |
Citations | PageRank | References |
3 | 0.40 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adam Viktorin | 1 | 29 | 16.76 |
| Roman Senkerik | 2 | 375 | 74.92 |
| Michal Pluhacek | 3 | 217 | 47.34 |
| Tomas Kadavy | 4 | 20 | 20.97 |
| Ales Zamuda | 5 | 400 | 18.26 |