New computer methods for global optimization
New computer methods for global optimization
Subdivision Direction Selection in Interval Methods for Global Optimization
SIAM Journal on Numerical Analysis
C++ Toolbox for Verified Scientific Computing I: Basic Numerical Problems
C++ Toolbox for Verified Scientific Computing I: Basic Numerical Problems
C-XSC: A C++ Class Library for Extended Scientific Computing
C-XSC: A C++ Class Library for Extended Scientific Computing
A Nonsmooth Global Optimization Technique Using Slopes: The One-Dimensional Case
Journal of Global Optimization
Multisection in Interval Branch-and-Bound Methods for Global Optimization – I. Theoretical Results
Journal of Global Optimization
New Subinterval Selection Criteria for Interval Global Optimization
Journal of Global Optimization
Journal of Global Optimization
Methods and Applications of Interval Analysis (SIAM Studies in Applied and Numerical Mathematics) (Siam Studies in Applied Mathematics, 2.)
Optimal Multisections in Interval Branch-and-Bound Methods of Global Optimization
Journal of Global Optimization
Comparison Between Baumann and Admissible Simplex Forms in Interval Analysis
Journal of Global Optimization
A second-order pruning step for verified global optimization
Journal of Global Optimization
Engineering Applications of Artificial Intelligence
On lower bounds using additively separable terms in interval b&b
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
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In this paper the kite inclusion function is presented for branch-and-bound type interval global optimization using at least gradient information. The basic idea comes from the simultaneous usage of the centered forms and the linear boundary value forms. We will show that the new technique is not worse and usually considerably better than these two. The best choice for the center of the kite inclusion will be given. The isotonicity and at least quadratical convergence hold and there is a pruning effect of the kite which is derived from the construction of the inclusion, thus more function evaluations are not needed to use it. A numerical investigation on large standard multiextremal test functions has been done to show the performance.