Constructing large feasible suboptimal intervals for constrained nonlinear optimization

DOI10.1007/BF02096403zbMath0843.90107MaRDI QIDQ1904721

Zelda B. Zabinsky, Tibor Csendes, Birna P. Kristinsdottir

Publication date: 1 February 1996

Published in: Annals of Operations Research (Search for Journal in Brave)

zbMATH Keywords

sensitivity analysisconstrained global optimizationconstrained nonlinear optimizationinclusion functionlarge feasible \(n\)-dimensional interval

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Sensitivity, stability, parametric optimization (90C31)

Related Items (3)

OPTIMIZATION AND THE MIRANDA APPROACH IN DETECTING HORSESHOE-TYPE CHAOS BY COMPUTER ⋮ Allocation of limited resources under quadratic constraints ⋮ A verified optimization technique to locate chaotic regions of Hénon systems

Uses Software

• C-XSC
• C-XSC 2.0

Cites Work

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• FORTRAN-SC. A study of a FORTRAN extension for engineering/scientific computation with access to ACRITH
• Interval method for bounding level sets: Revisited and tested with global optimization problems
• Constrained global optimization: algorithms and applications
• An interval method for bounding level sets of parameter estimation problems
• A collection of test problems for constrained global optimization algorithms
• An interval branch and bound algorithm for bound constrained optimization problems
• Experiments using interval analysis for solving a circuit design problem
• The use of augmented lagrangian functions for sensitivity analysis in nonlinear programming
• Sensitivity analysis for nonlinear programming using penalty methods
• A new interval method for locating the boundary of level sets

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