A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems
M. Tavana, V. Hajipour, M. Alaghebandha, D. Di Caprio, Machine Learning with Applications 11 (2023).
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Journal Article
| Published
| English
Author
Tavana, MadjidLibreCat;
Hajipour, Vahid;
Alaghebandha, Mohammad;
Di Caprio, Debora
Keywords
Publishing Year
Journal Title
Machine Learning with Applications
Volume
11
Article Number
100445
ISSN
LibreCat-ID
Cite this
Tavana M, Hajipour V, Alaghebandha M, Di Caprio D. A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems. Machine Learning with Applications. 2023;11. doi:10.1016/j.mlwa.2022.100445
Tavana, M., Hajipour, V., Alaghebandha, M., & Di Caprio, D. (2023). A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems. Machine Learning with Applications, 11, Article 100445. https://doi.org/10.1016/j.mlwa.2022.100445
@article{Tavana_Hajipour_Alaghebandha_Di Caprio_2023, title={A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems}, volume={11}, DOI={10.1016/j.mlwa.2022.100445}, number={100445}, journal={Machine Learning with Applications}, publisher={Elsevier BV}, author={Tavana, Madjid and Hajipour, Vahid and Alaghebandha, Mohammad and Di Caprio, Debora}, year={2023} }
Tavana, Madjid, Vahid Hajipour, Mohammad Alaghebandha, and Debora Di Caprio. “A Bi-Objective Hybrid Vibration Damping Optimization Model for Synchronous Flow Shop Scheduling Problems.” Machine Learning with Applications 11 (2023). https://doi.org/10.1016/j.mlwa.2022.100445.
M. Tavana, V. Hajipour, M. Alaghebandha, and D. Di Caprio, “A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems,” Machine Learning with Applications, vol. 11, Art. no. 100445, 2023, doi: 10.1016/j.mlwa.2022.100445.
Tavana, Madjid, et al. “A Bi-Objective Hybrid Vibration Damping Optimization Model for Synchronous Flow Shop Scheduling Problems.” Machine Learning with Applications, vol. 11, 100445, Elsevier BV, 2023, doi:10.1016/j.mlwa.2022.100445.
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