A performance study of genetic algorithms-based quantum approximate optimisation in the context of power networks

Tools

Chiatto, A, Alizadeh, A, Acampora, G, Vitiello, A, Pourabdollah, A ORCID: https://orcid.org/0000-0001-7737-1393 and Lotfi, A ORCID: https://orcid.org/0000-0002-5139-6565, 2025. A performance study of genetic algorithms-based quantum approximate optimisation in the context of power networks. In: Zheng, H, Glass, D, Mulvenna, M, Liu, J and Wang, H, eds., Advances in computational intelligence systems: contributions presented at the 23rd UK Workshop on Computational Intelligence (UKCI 2024), September 2-4, 2024, Ulster University, Belfast, UK. Advances in Intelligent Systems and Computing . Cham: Springer, pp. 303-314. ISBN 9783031788567

Full text not available from this repository.

Official URL: https://doi.org/10.1007/978-3-031-78857-4_23

Item Type:	Chapter in book
Description:	Paper presented at 23rd UK Workshop on Computational Intelligence (UKCI 2024), September 2-4, 2024, Ulster University, Belfast.
Creators:	Chiatto, A., Alizadeh, A., Acampora, G., Vitiello, A., Pourabdollah, A. and Lotfi, A.
Publisher:	Springer
Place of Publication:	Cham
Date:	8 January 2025
ISBN:	9783031788567
Identifiers:	Number Type 10.1007/978-3-031-78857-4_23 DOI 2347184 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Borcherds
Date Added:	11 Mar 2025 13:36
Last Modified:	11 Mar 2025 13:36
URI:	https://irep.ntu.ac.uk/id/eprint/53232