Hybrid Constraint-Aware Genetic Optimization for Structurally Coupled Resource Allocation, User Scheduling, and Grouping: An SBMA Case Study

Xiangyu Yang, Jianjian Wu, Jun Wang

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DOI: 10.3390/s26206586
Published: 2026-10-17
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s26206586,
  title = {Hybrid Constraint-Aware Genetic Optimization for Structurally Coupled Resource Allocation, User Scheduling, and Grouping: An SBMA Case Study},
  author = {Xiangyu Yang and Jianjian Wu and Jun Wang},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26206586},
  url = {https://doi.org/10.3390/s26206586}
}

RIS

TY  - JOUR
TI  - Hybrid Constraint-Aware Genetic Optimization for Structurally Coupled Resource Allocation, User Scheduling, and Grouping: An SBMA Case Study
AU  - Xiangyu Yang
AU  - Jianjian Wu
AU  - Jun Wang
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26206586
UR  - https://doi.org/10.3390/s26206586
ER  -

APA

Yang, X., Wu, J., & Wang, J. (2026). Hybrid Constraint-Aware Genetic Optimization for Structurally Coupled Resource Allocation, User Scheduling, and Grouping: An SBMA Case Study. Sensors. https://doi.org/10.3390/s26206586

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crossref · retrieved 2026-11-10T07:13:36.751Z