Numerical solution for bounding feasible point sets

DOI10.1016/S0377-0427(02)00912-3zbMath1022.65068MaRDI QIDQ1398432

Peiliang Xu

Publication date: 29 July 2003

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

zbMATH Keywords

algorithmsglobal optimizationnumerical examplesmultisplittinginterval mathematicsmultisectionfeasible point setsystem of nonlinear and nonconvex inequalities

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

Related Items (2)

Iterative algorithm for solving a class of convex feasibility problem ⋮ A hybrid global optimization method: The multi-dimensional case

Uses Software

• INTOPT_90

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Derived eigenvalues of symmetric matrices, with applications to distance geometry
• Global optimization using interval analysis - the multi-dimensional case
• Enlarging the region of convergence of Newton's method for constrained optimization
• Newton's method for nonlinear inequalities
• On proving existence of feasible points in equality constrained optimization problems
• An interval algorithm for constrained global optimization
• Safe starting regions by fixed points and tightening
• Rigorous global search: continuous problems
• Heuristic search and pruning in polynomial constraints satisfaction
• Multisection in interval branch-and-bound methods for global optimization. I: Theoretical results
• A new multisection technique in interval methods for global optimization
• A hybrid global optimization method: The one-dimensional case
• Deterministic global optimization. Theory, methods and applications
• Newton's method for the solution of systems of equalities and inequalities
• Extension of Newton's method to nonlinear functions with values in a cone
• A Gauss-Newton Approach to Solving Generalized Inequalities
• Solving Polynomial Systems Using a Branch and Prune Approach
• A Trust-Region Approach to Nonlinear Systems of Equalities and Inequalities
• Equation of State Calculations by Fast Computing Machines
• Gradient methods for solving equations and inequalities
• Convex analysis and global optimization
• Interval constraint propagation with application to bounded-error estimation
• Introduction to global optimization.

This page was built for publication: Numerical solution for bounding feasible point sets