On proving existence of feasible points in equality constrained optimization problems

DOI10.1007/BF02680551zbMath0949.90089OpenAlexW2146424631MaRDI QIDQ1290652

Ralph Baker Kearfott

Publication date: 28 June 1999

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02680551

zbMATH Keywords

bound constraintsinterval computationsconstrained global optimizationverified computations

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Interval and finite arithmetic (65G30)

Related Items

Linear and parabolic relaxations for quadratic constraints, On verified numerical computations in convex programming, A branch and bound algorithm for quantified quadratic programming, Numerical solution for bounding feasible point sets, Obtaining the efficient set of nonlinear biobjective optimization problems via interval branch-and-bound methods, Branch-and-lift algorithm for deterministic global optimization in nonlinear optimal control, A continuous location model for siting a non-noxious undesirable facility within a geographical region, On rigorous upper bounds to a global optimum, New interval methods for constrained global optimization, Rigorous verification of feasibility, Convergent upper bounds in global minimization with nonlinear equality constraints, Mathematically rigorous global optimization in floating-point arithmetic, Constraint aggregation for rigorous global optimization, Some observations on exclusion regions in branch and bound algorithms, Deterministic upper bounds for spatial branch-and-bound methods in global minimization with nonconvex constraints

Uses Software

• LANCELOT
• INTOPT_90

Cites Work

• A collection of test problems for constrained global optimization algorithms
• An interval algorithm for constrained global optimization
• Rigorous global search: continuous problems
• Epsilon-inflation in verification algorithms
• Preconditioners for the Interval Gauss–Seidel Method
• Interval Methods for Systems of Equations
• A Fortran 90 environment for research and prototyping of enclosure algorithms for nonlinear equations and global optimization
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