Name
Abstract | ||
|---|---|---|
Differential Evolution (DE) is a robust optimization algorithm, but it suffers from the stagnation problem in which individuals may not escape from a local optimum. In this article, we proposed a new Cauchy mutation using multiple exponential recombination, self-adaptive parameter control, and linear failure threshold reduction. The proposed method is a simple yet efficient to mitigate the stagnation problem, and it can improve the convergence speed of DE. Our experimental results show that the proposed method can find more accurate solutions to complicated problems.
|
Year | Venue | Field |
|---|---|---|
2018 | GECCO (Companion) | Convergence (routing),Mathematical optimization,Exponential function,Global optimization,Computer science,Robust optimization,Local optimum,Differential evolution,Cauchy mutation,Parameter control |
DocType | ISBN | Citations |
Conference | 978-1-4503-5764-7 | 0 |
PageRank | References | Authors |
0.34 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tae Jong Choi | 1 | 5 | 2.47 |
| Chang Wook Ahn | 2 | 759 | 60.88 |