A novel hybrid multi operator evolutionary algorithm for dynamic distributed generation optimization and optimal feeder reconfiguration
- DOI
- 10.1038/s41598-025-17776-7
- Published
- 2025-09-24
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-17776-7,
title = {A novel hybrid multi operator evolutionary algorithm for dynamic distributed generation optimization and optimal feeder reconfiguration},
author = {Aamir Ali and Abdul Sattar Saand and Shoaib Ali and Rizwan A. Siddiqui and Mohsin Ali Koondhar and Lutfi Albasha and Faisal Alsaif},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-17776-7},
url = {https://doi.org/10.1038/s41598-025-17776-7}
}RIS
TY - JOUR TI - A novel hybrid multi operator evolutionary algorithm for dynamic distributed generation optimization and optimal feeder reconfiguration AU - Aamir Ali AU - Abdul Sattar Saand AU - Shoaib Ali AU - Rizwan A. Siddiqui AU - Mohsin Ali Koondhar AU - Lutfi Albasha AU - Faisal Alsaif PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-17776-7 UR - https://doi.org/10.1038/s41598-025-17776-7 ER -
APA
Ali, A., Saand, A. S., Ali, S., Siddiqui, R. A., Koondhar, M. A., Albasha, L., & Alsaif, F. (2025). A novel hybrid multi operator evolutionary algorithm for dynamic distributed generation optimization and optimal feeder reconfiguration. Scientific Reports. https://doi.org/10.1038/s41598-025-17776-7
Source records
- crossref · retrieved 2026-09-26T04:45:43.394Z