TY  - THES
AU  - Blázsik, Zoltán
TI  - Domináló csúcsok szerepe hálózati folyamatok tervezésében
PB  - Szegedi Tudományegyetem (SZTE)
PY  - 2009
SP  - 104
UR  - https://m2.mtmt.hu/api/publication/21596389
ID  - 21596389
LA  - Hungarian
DB  - MTMT
ER  - 

TY  - THES
AU  - Bánhelyi, Balázs
TI  - Dinamikus rendszerek kaotikusságának és stabilitásának vizsgálata megbízható számítógépes módszerekkel
PB  - Szegedi Tudományegyetem (SZTE)
PY  - 2008
SP  - 114
UR  - https://m2.mtmt.hu/api/publication/23850247
ID  - 23850247
LA  - Hungarian
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Martínez, J A
AU  - Casado, L G
AU  - García, I
AU  - Sergeyev, Ya D
AU  - Gazdag-Tóth, Boglárka
TI  - On an efficient use of gradient information for accelerating interval global optimization algorithms
JF  - NUMERICAL ALGORITHMS
J2  - NUMER ALGORITHMS
VL  - 37
PY  - 2004
IS  - 1-4
SP  - 61
EP  - 69
PG  - 9
SN  - 1017-1398
DO  - 10.1023/B:NUMA.0000049456.81410.fc
UR  - https://m2.mtmt.hu/api/publication/1192185
ID  - 1192185
N1  - Comp. Arch. and Electronics Dept., Univ. of Almeria Cta. Sacramento SN, 04120 Almería, Spain, Spain            
            DEIS, Universita' Della Calabria, Italy, Univ. Nizhni Novgorod, N., Italy            
            University of Szeged, Department of Applied Informatics, H-6701 Szeged, Hungary, Hungary            
            Cited By :9            
            Export Date: 8 April 2020            
            Correspondence Address: Comp. Arch. and Electronics Dept., Univ. of Almeria Cta. Sacramento SN, 04120 Almería, SpainSpain; email: leo@ace.ual.es
Cited By :9            
            Export Date: 27 July 2021
AB  - 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.
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Martínez, J A
AU  - Casado, L G
AU  - García, I
AU  - Gazdag-Tóth, Boglárka
ED  - Floudas, C A
ED  - Pardalos, P M
TI  - AMIGO: Advanced Multidimensional Interval Analysis Global Optimization algorithm
T2  - Frontiers in Global Optimization
PB  - Kluwer Academic Publishers
CY  - London
CY  - Dordrecht
CY  - Boston (MA), Massachusetts
SN  - 1402076991
T3  - Nonconvex Optimization and Applications ; 74.
PY  - 2003
SP  - 313
EP  - 326
PG  - 14
DO  - 10.1007/978-1-4613-0251-3_17
UR  - https://m2.mtmt.hu/api/publication/1206394
ID  - 1206394
AB  - 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.
LA  - English
DB  - MTMT
ER  -