Cargando…
An Improved CMA-ES for Solving Large Scale Optimization Problem
In solving large scale optimization problems, CMA-ES has the disadvantages of high complexity and premature stagnation. To solve this problem, this paper proposes an improved CMA-ES, called GI-ES, for large-scale optimization problems. GI-ES uses all the historical information of the previous genera...
Autores principales: | Jin, Jin, Yang, Chuan, Zhang, Yi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354820/ http://dx.doi.org/10.1007/978-3-030-53956-6_34 |
Ejemplares similares
-
On the use of element-by-element preconditioners to solve large scale partially separable optimization problemes
por: Dayde, M J, et al.
Publicado: (1995) -
Parameter Optimization Using Covariance Matrix Adaptation—Evolutionary Strategy (CMA-ES), an Approach to Investigate Differences in Channel Properties Between Neuron Subtypes
por: Jȩdrzejewski-Szmek, Zbigniew, et al.
Publicado: (2018) -
An Improved Chicken Swarm Optimization Algorithm for Solving Multimodal Optimization Problems
por: Liang, Jianhui, et al.
Publicado: (2022) -
Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method
por: Bruckner, Florian, et al.
Publicado: (2017) -
Recent Developments at the CMA: 2019–2020
por: Havell, Richard, et al.
Publicado: (2020)