A nonmonotone trust-region method of conic model for unconstrained optimization

DOI10.1016/j.cam.2007.07.038zbMath1151.65055OpenAlexW2119994280MaRDI QIDQ939515

Shao-Jian Qu, Ke-Cun Zhang, Jian Zhang

Publication date: 22 August 2008

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

Full work available at URL: https://doi.org/10.1016/j.cam.2007.07.038

zbMATH Keywords

unconstrained optimizationnumerical examplesconic modeltrust-region methodnonmonotone technique

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Interior-point methods (90C51)

Related Items

A new nonmonotone trust-region method of conic model for solving unconstrained optimization ⋮ A nonmonotone adaptive trust region method for unconstrained optimization based on conic model ⋮ A new modified nonmonotone adaptive trust region method for unconstrained optimization ⋮ A nonmonotone adaptive trust region method based on conic model for unconstrained optimization ⋮ Combining nonmonotone conic trust region and line search techniques for unconstrained optimization ⋮ A modified ODE-based algorithm for unconstrained optimization problems ⋮ A new hybrid method for nonlinear complementarity problems ⋮ A nonmonotone conic trust region method based on line search for solving unconstrained optimization ⋮ A new self-adaptive trust region method for unconstrained optimization

Uses Software

• minpack

Cites Work

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• A nonmonotone trust region method for unconstrained optimization
• A conic trust-region method for optimization with nonlinear equality and inequality constrains via active-set strategy
• A nonmonotone adaptive trust region method and its convergence
• Deriving collinear scaling algorithms as extensions of quasi-Newton methods and the local convergence of DFP- and BFGS-related collinear scaling algorithms
• On the global convergence of trust region algorithms for unconstrained minimization
• A Family of Trust-Region-Based Algorithms for Unconstrained Minimization with Strong Global Convergence Properties
• Conic Approximations and Collinear Scalings for Optimizers
• The Q-Superlinear Convergence of a Collinear Scaling Algorithm for Unconstrained Optimization
• Testing Unconstrained Optimization Software
• A Nonmonotone Line Search Technique for Newton’s Method
• A nonmonotone trust region method for nonlinear programming with simple bound constraints