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Cited by 16
Evaluation Ranges of Functions using Balanced Random Interval Arithmetic

2011 Fifth International Conference on Genetic and Evolutionary Computing
Kuo-Kun Tseng, Wei Wei, Jeng-Shyang Pan, Chih-Yu Hsu, Shuo-Tsung Chen
https://doi.org/10.1109/ICGEC.2011.101
Conference  (2011), p. 369
A Spatial Branch-and-Bound Framework for the Global Optimization of Kinetic Models of Metabolic Networks
C. Pozo, G. Guillén-Gosálbez, A. Sorribas, L. Jiménez
https://doi.org/10.1021/ie101368k
Journal  Industrial & Engineering Chemistry Research Volume 50, Issue 9 (2011), p. 5225
A Survey of Methods for the Estimation Ranges of Functions Using Interval Arithmetic
Julius Žilinskas, Ian David Lockhart Bogle
https://doi.org/10.1007/978-0-387-36721-7_6
Book  Optimization and Its Applications (Models and Algorithms for Global Optimization) Volume 4 (2007), p. 97
A review of recent advances in global optimization
C. A. Floudas, C. E. Gounaris
https://doi.org/10.1007/s10898-008-9332-8
Journal  Journal of Global Optimization Volume 45, Issue 1 (2009), p. 3
An Interval Partitioning Approach for Continuous Constrained Optimization
Chandra Sekhar Pedamallu, Linet Özdamar, Tibor Csendes
https://doi.org/10.1007/978-0-387-36721-7_5
Book  Optimization and Its Applications (Models and Algorithms for Global Optimization) Volume 4 (2007), p. 73
Balanced Random and Adaptive Interval Arithmetic for Systems of Linear Interval Equations
J. Žilinskas, I. D. L. Bogle
https://doi.org/10.1007/978-0-85729-338-1_29
Book  (2004), p. 347
Balanced random interval arithmetic
Julius Zilinskas, Ian David Lockhart Bogle
https://doi.org/10.1016/j.compchemeng.2004.02.020
Journal  Computers & Chemical Engineering Volume 28, Issue 5 (2004), p. 839
Balanced random interval arithmetic in market model estimation
Julius Zilinskas, Ian David Lockhart Bogle
https://doi.org/10.1016/j.ejor.2005.02.013
Journal  European Journal of Operational Research Volume 175, Issue 3 (2006), p. 1367
Dynamic Global Optimization Methods for Determining Guaranteed Solutions in Chemical Engineering
Carlos Pérez-Galván, I. David L. Bogle
https://doi.org/10.1007/978-3-319-29975-4_10
Book  Springer Optimization and Its Applications (Advances in Stochastic and Deterministic Global Optimization) Volume 107 (2016), p. 181
GLOBAL OPTIMIZATION USING THE BRANCH‐AND‐BOUND ALGORITHM WITH A COMBINATION OF LIPSCHITZ BOUNDS OVER SIMPLICES
Remigijus Paulavičius, Julius Žilinskas
https://doi.org/10.3846/1392-8619.2009.15.310-325
Journal  Technological and Economic Development of Economy Volume 15, Issue 2 (2009), p. 310
Global optimization in the 21st century: Advances and challenges
C.A. Floudas, I.G. Akrotirianakis, S. Caratzoulas, C.A. Meyer, J. Kallrath
https://doi.org/10.1016/j.compchemeng.2005.02.006
Journal  Computers & Chemical Engineering Volume 29, Issue 6 (2005), p. 1185
Global optimization in the 21st century: Advances and challenges
C.A. Floudas, I.G. Akrotiriankis, S. Caratzoulas, C.A. Meyer, J. Kallrath
https://doi.org/10.1016/S1570-7946(04)80082-8
Book  Computer Aided Chemical Engineering (European Symposium on Computer-Aided Process Engineering-14, 37th European Symposium of the Working Party on Computer-Aided Process Engineering) Volume 18 (2004), p. 23
IMPROVED LIPSCHITZ BOUNDS WITH THE FIRST NORM FOR FUNCTION VALUES OVER MULTIDIMENSIONAL SIMPLEX
Remigijus Paulavičius, Julius Žilinskas
https://doi.org/10.3846/1392-6292.2008.13.553-563
Journal  Mathematical Modelling and Analysis Volume 13, Issue 4 (2008), p. 553
Numerical Health Check of Industrial Simulation Codes from HPC Environments to New Hardware Technologies
Christophe Denis
https://doi.org/10.1007/978-3-642-14403-5_35
Book  Lecture Notes in Computer Science (Parallel Processing and Applied Mathematics) Volume 6068 (2010), p. 330
On Efficiency of Tightening Bounds in Interval Global Optimization
Antanas Žilinskas, Julius Žilinskas
https://doi.org/10.1007/11558958_22
Book  Lecture Notes in Computer Science (Applied Parallel Computing. State of the Art in Scientific Computing) Volume 3732 (2006), p. 197
Research challenges, opportunities and synergism in systems engineering and computational biology
Christodoulos A. Floudas
https://doi.org/10.1002/aic.10620
Journal  AIChE Journal Volume 51, Issue 7 (2005), p. 1872


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