Substitution secant/finite difference method to large sparse minimax problems
DOI10.3934/jimo.2014.10.637zbMath1281.90085OpenAlexW2029087793MaRDI QIDQ380609
Qiang Su, Jiazhen Huo, Tao Dai, Chunming Ye, Yan Gao, Jun-Xiang Li
Publication date: 14 November 2013
Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/jimo.2014.10.637
partitionminimax problemnondifferentiable optimizationfinite differencesecant methodsparsitysubstitution
Large-scale problems in mathematical programming (90C06) Minimax problems in mathematical programming (90C47) Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Optimality conditions for minimax problems (49K35)
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- Inexact smoothing method for large scale minimax optimization
- A nonlinear augmented Lagrangian for constrained minimax problems
- Inexact trust region PGC method for large sparse unconstrained optimization
- On the accurate identification of active set for constrained minimax problems
- On solving large-scale finite minimax problems using exponential smoothing
- Algorithms with adaptive smoothing for finite minimax problems
- Nonmonotone algorithm for minimax optimization problems
- A smoothing trust-region Newton-CG method for minimax problem
- An algorithm based on active sets and smoothing for discretized semi-infinite minimax problems
- An interior-point algorithm for nonlinear minimax problems
- A sequential quadratically constrained quadratic programming method for unconstrained minimax problems
- Optimization. Algorithms and consistent approximations
- Rate of convergence analysis of discretization and smoothing algorithms for semiinfinite minimax problems
- Superlinearly convergent algorithm for min-max problems
- Feasible generalized monotone line search SQP algorithm for nonlinear minimax problems with inequality constraints
- The substitution secant/finite difference method for large scale sparse unconstrained optimization
- Portfolio Optimization Under a Minimax Rule
- A globally convergent algorithm with adaptively refined discretization for semi-infinite optimization problems arising in engineering design
- Estimation of sparse hessian matrices and graph coloring problems
- Optimization and nonsmooth analysis
- Adaptive control of ARMA plants using worst-case design by semi-infinite optimization
- On the Estimation of Sparse Hessian Matrices
- Variable metric methods for minimizing a class of nondifferentiable functions
- A Projected Lagrangian Algorithm for Nonlinear Minimax Optimization
- On the Extension of Newton’s Method to Semi-Infinite Minimax Problems
- Perturbed Kuhn-Tucker points and rates of convergence for a class of nonlinear-programming algorithms
- Combined phase I—phase II methods of feasible directions
- Numerical Optimization
- Derivative-free optimization methods for finite minimax problems
- Min‐Max quickest path problems
- A Derivative-Free Algorithm for Linearly Constrained Finite Minimax Problems
- Convex Analysis
- Smoothing method for minimax problems
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