MOEA/D with chain-based random local search for sparse optimization

DOI10.1007/S00500-018-3460-YzbMath1402.90169OpenAlexW2892164586WikidataQ129295904 ScholiaQ129295904MaRDI QIDQ1626237

Hui Li, Qingfu Zhang, Jianyong Sun, Mingyang Wang

Publication date: 27 November 2018

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-018-3460-y

zbMATH Keywords

multiobjective optimizationsparse optimizationMOEA/DCRLSHALFSPLS

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• MOEA/D

Cites Work

• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• A multiobjective evolutionary algorithm based on decomposition with normal boundary intersection for traffic grooming in optical networks
• Iterative hard thresholding for compressed sensing
• Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
• <formula formulatype="inline"><tex Notation="TeX">$L_{1/2}$</tex> </formula> Regularization: Convergence of Iterative Half Thresholding Algorithm
• Sparse Approximate Solutions to Linear Systems
• De-noising by soft-thresholding
• Matching pursuits with time-frequency dictionaries
• Compressed sensing
• Complex wavelets for shift invariant analysis and filtering of signals

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