Tensor decomposition-based alternate sub-population evolution for large-scale many-objective optimization
DOI10.1016/j.ins.2021.04.003zbMath1527.90208OpenAlexW3145175715MaRDI QIDQ6092023
No author found.
Publication date: 23 November 2023
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2021.04.003
Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Multi-objective and goal programming (90C29) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59) Eigenvalues, singular values, and eigenvectors (15A18) Multilinear algebra, tensor calculus (15A69)
Cites Work
- A nature inspired parameter tuning approach to cascade control for hydraulically driven parallel robot platform
- Solving large-scale many-objective optimization problems by covariance matrix adaptation evolution strategy with scalable small subpopulations
- Tensor-based mathematical framework and new centralities for temporal multilayer networks
- Rapid compressed sensing reconstruction: a semi-tensor product approach
- Tensor \(N\)-tubal rank and its convex relaxation for low-rank tensor recovery
- High-order tensor estimation via trains of coupled third-order CP and Tucker decompositions
- A sparse rank-1 approximation algorithm for high-order tensors
- An unsupervised fault diagnosis method for rolling bearing using STFT and generative neural networks
- AREA: an adaptive reference-set based evolutionary algorithm for multiobjective optimisation
- Enhancing MOEA/D with information feedback models for large-scale many-objective optimization
- An adaptive clustering-based evolutionary algorithm for many-objective optimization problems
- A Multilinear Singular Value Decomposition
This page was built for publication: Tensor decomposition-based alternate sub-population evolution for large-scale many-objective optimization
