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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Caio, P.  & Silva, C. J.  (2025). Application of indirect methods to optimal control problems in epidemiology. In Antonio Pedro Aguiar, Paula Rocha Malonek, Vítor Hugo Pinto, Fernando A. C. C. Fontes, Roman Chertovskih (Ed.), CONTROLO 2024: Proceedings of the 16th APCA International Conference on Automatic Control and Soft Computing. (pp. 444-454). Porto: Springer.
Exportar Referência (IEEE) 
P. Caio and C. J. Silva,  "Application of indirect methods to optimal control problems in epidemiology", in CONTROLO 2024: Proc. of the 16th APCA Int. Conf. on Automatic Control and Soft Computing, Antonio Pedro Aguiar, Paula Rocha Malonek, Vítor Hugo Pinto, Fernando A. C. C. Fontes, Roman Chertovskih, Ed., Porto, Springer, 2025, vol. 1325, pp. 444-454
Exportar BibTeX 
@inproceedings{caio2025_1777801950642,
	author = "Caio, P.  and Silva, C. J. ",
	title = "Application of indirect methods to optimal control problems in epidemiology",
	booktitle = "CONTROLO 2024: Proceedings of the 16th APCA International Conference on Automatic Control and Soft Computing",
	year = "2025",
	editor = "Antonio Pedro Aguiar, Paula Rocha Malonek, Vítor Hugo Pinto, Fernando A. C. C. Fontes, Roman Chertovskih",
	volume = "1325",
	number = "",
	series = "",
	doi = "10.1007/978-3-031-81724-3_40",
	pages = "444-454",
	publisher = "Springer",
	address = "Porto",
	organization = "",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-81724-3_40"
}
Exportar RIS 
TY  - CPAPER
TI  - Application of indirect methods to optimal control problems in epidemiology
T2  - CONTROLO 2024: Proceedings of the 16th APCA International Conference on Automatic Control and Soft Computing
VL  - 1325
AU  - Caio, P. 
AU  - Silva, C. J. 
PY  - 2025
SP  - 444-454
SN  - 1876-1100
DO  - 10.1007/978-3-031-81724-3_40
CY  - Porto
UR  - https://link.springer.com/chapter/10.1007/978-3-031-81724-3_40
AB  - Currently most of the numerical resolution of optimal control problems is done using direct methods where the increase accuracy of indirect methods is overshadowed by the necessary analytical derivation required beforehand. With recent developments from the control-toolbox ecosystem team the application of indirect methods as become more streamline enabling a wider range of problems to be solved, like, for example, optimal control problems applied to the transmission of infectious diseases. In this work, we aim to extend the application of indirect methods to optimal control problems applied to epidemiological models, using the control-toolbox
ER  -