Results 281 to 290 of about 286,749 (305)
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Interval-majorant method and global optimization
Computing, 1989zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shen Zuhe, Michael C. Eiermann
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Comment on “Method of Constrained Global Optimization”
Physical Review Letters, 1995A Comment on the Letter by Eric Lewin Altschuler [ital et] [ital al]., Phys. Rev. Lett. [bold 72], 2671 (1994).
, Erber, , Hockney
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A hybrid method for quantum global optimization
Journal of Global Optimization, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yipeng Liu, Gary J. Koehler
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Global descent method for constrained continuous global optimization
Applied Mathematics and Computation, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Amine Ketfi-Cherif, Abdelkader Ziadi
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On a decomposition method for nonconvex global optimization
Optimization Letters, 2006The author presents a rigorous framework for convergence results for the branch and bound decomposition method in nonconvex global optimization. The essential assumptions needed to prove convergence for the branch and bound decomposition scheme with Lagrangian bounds are discussed in detail.
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Cross-Hill: A heuristic method for global optimization
Applied Mathematics and Computation, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tingting Wu 0001, Deren Han, Yi Xu
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Two-Phase Methods for Global Optimization
2002Virtually all methods for global optimization consist of two phases: a global phase, aimed at thorough exploration of the feasible region or subsets of the feasible region where it is known the global optimum will be found, and a local phase aimed at locally improving the approximation to some local optima.
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A Global Search Method for Discrete Stochastic Optimization
SIAM Journal on Optimization, 1996Summary: This paper is concerned with the problem of optimizing the performance of a stochastic system over a finite set of alternatives in situations where the performance of the system cannot be evaluated analytically, but must be estimated or measured, for instance, through simulation.
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On Generalizing Lipschitz Global Methods forMultiobjective Optimization
2015Lipschitz global methods for single-objective optimization can represent the optimal solutions with desired accuracy. In this paper, we highlight some directions on how the Lipschitz global methods can be extended as faithfully as possible to multiobjective optimization problems.
Alberto Lovison, Markus E. Hartikainen
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Global optimization methods for high-dimensional problems
European Journal of Operational Research, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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