A variant of the Topkis-Veinott method for solving inequality constrained optimization problems

DOI10.1007/s002459911015zbMath0952.65049OpenAlexW2017322721MaRDI QIDQ1568186

N. Delaunay

Publication date: 2000

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

Full work available at URL: http://hdl.handle.net/2027.42/3660

zbMATH Keywords

algorithmglobal convergencenumerical examplesinequality constrained optimization problemsTopkis-Veinott feasible descent direction method

Mathematics Subject Classification ID

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

Related Items (max. 100)

Elastoplastic analysis of structures under uncertainty: model and solution methods¹ ⋮ A variant of SQP method for inequality constrained optimization and its global convergence ⋮ BI-LEVEL PROGRAMMING APPROACH TO OPTIMAL STRATEGY FOR VENDOR-MANAGED INVENTORY PROBLEMS UNDER RANDOM DEMAND ⋮ An efficient sequential quadratic programming algorithm for nonlinear programming ⋮ A validation and verification tool for global optimization solvers ⋮ Optimal pricing and ordering in global supply chain management with constraints under random demand ⋮ On differentiability properties of player convex generalized Nash equilibrium problems

This page was built for publication: A variant of the Topkis-Veinott method for solving inequality constrained optimization problems