@mastersthesis{MTMT:21596389,
	title = {Domináló csúcsok szerepe hálózati folyamatok tervezésében},
	url = {https://m2.mtmt.hu/api/publication/21596389},
	author = {Blázsik, Zoltán},
	publisher = {SZTE},
	unique-id = {21596389},
	year = {2009},
	orcid-numbers = {Blázsik, Zoltán/0000-0002-8548-1995}
}

@mastersthesis{MTMT:23850247,
	title = {Dinamikus rendszerek kaotikusságának és stabilitásának vizsgálata megbízható számítógépes módszerekkel},
	url = {https://m2.mtmt.hu/api/publication/23850247},
	author = {Bánhelyi, Balázs},
	publisher = {SZTE},
	unique-id = {23850247},
	year = {2008},
	orcid-numbers = {Bánhelyi, Balázs/0000-0003-4408-9054}
}

@article{MTMT:1192185,
	title = {On an efficient use of gradient information for accelerating interval global optimization algorithms},
	url = {https://m2.mtmt.hu/api/publication/1192185},
	author = {Martínez, J A and Casado, L G and García, I and Sergeyev, Ya D and Gazdag-Tóth, Boglárka},
	doi = {10.1023/B:NUMA.0000049456.81410.fc},
	journal-iso = {NUMER ALGORITHMS},
	journal = {NUMERICAL ALGORITHMS},
	volume = {37},
	unique-id = {1192185},
	issn = {1017-1398},
	abstract = {This paper analyzes and evaluates an efficient n-dimensional global optimization algorithm. It is a natural n-dimensional extension of the algorithm of Casado et al. [1]. This algorithm takes advantage of all available information to estimate better bounds of the function. Numerical comparison made on a wide set of multiextremal test functions has shown that on average the new algorithm works faster than a traditional interval analysis global optimization method.},
	keywords = {branch-and-bound; Interval arithmetic; Global optimization},
	year = {2004},
	eissn = {1572-9265},
	pages = {61-69},
	orcid-numbers = {Gazdag-Tóth, Boglárka/0000-0002-0927-111X}
}

@inproceedings{MTMT:1206394,
	title = {AMIGO: Advanced Multidimensional Interval Analysis Global Optimization algorithm},
	url = {https://m2.mtmt.hu/api/publication/1206394},
	author = {Martínez, J A and Casado, L G and García, I and Gazdag-Tóth, Boglárka},
	booktitle = {Frontiers in Global Optimization},
	doi = {10.1007/978-1-4613-0251-3_17},
	unique-id = {1206394},
	abstract = {This paper analyzes and evaluates an efficient n-dimensional global optimization algorithm. It is an extended version of the algorithm of Casado et al. [1]. This algorithm takes advantage of all available information to estimate better bounds of the function. Numerical comparison made on a class of multiextremal test functions has shown that on average the new algorithm works faster than a traditional gradient based interval analysis global optimization method.},
	keywords = {Computer Science, Theory & Methods; Operations Research & Management Science},
	year = {2003},
	pages = {313-326},
	orcid-numbers = {Gazdag-Tóth, Boglárka/0000-0002-0927-111X}
}