- Referenced in 55 articles
- linear systems is a difficult, nonconvex, nonsmooth optimization problem when the order of the controller ... depends on a hybrid algorithm for nonsmooth, nonconvex optimization based on quasi-Newton updating...
- Referenced in 106 articles
- robust gradient sampling algorithm for nonsmooth, nonconvex optimization The authors describe a practical and robust...
- Referenced in 35 articles
- memory bundle method for large-scale nonsmooth optimization Many practical optimization problems involve nonsmooth (that ... hand, none of the current general nonsmooth optimization methods is efficient in large-scale settings ... metric based bundle method for nonsmooth large-scale optimization. In addition, we introduce ... academic test problems for large-scale nonsmooth minimization. Finally, we give some encouraging results from...
- Referenced in 19 articles
- Multiobjective proximal bundle method for nonconvex nonsmooth optimization: Fortran subroutine MPBNGC 2.0. MPBNGC...
- Referenced in 17 articles
- linesearch-based derivative-free approach for nonsmooth constrained optimization. In this paper, we propose ... linesearch-based methods for nonsmooth constrained optimization problems when first-order information on the problem ... constrained optimization problems where both objective function and constraints can possibly be nonsmooth. In this...
- Referenced in 8 articles
- data fitting, min-max programming, multicriteria optimization, nonsmooth optimization, quadratic programming, or linear programming, subject...
- Referenced in 8 articles
- Nonsmooth optimization (NSO) refers to the general problem of minimizing (or maximizing) functions that ... regularity assumptions upon the functions to be optimized, it can not be directly utilized. However ... functions involved in practical applications are often nonsmooth. That is, they are not necessarily differentiable ... introduce the basic concepts of nonsmooth analysis and optimization...
- Referenced in 10 articles
- shown to perform well on many local optimization problems, and problems with linear objective functions ... genetic algorithm, Nonsmooth Optimization by Mesh Adaptive Direct Search (NOMAD), SO-MI (M”uller...
- Referenced in 9 articles
- derivative-free approach to constrained multiobjective nonsmooth optimization. In this work, we consider multiobjective optimization...
- Referenced in 71 articles
- linear constraints. Subroutine PMIN, intended for minimax optimization, is based on a sequential quadratic programming ... Subroutines PBUN and PNEW, intended for general nonsmooth problems, are based on bundle-type methods...
- Referenced in 32 articles
- smooth optimization problems, sometimes can be achieved even on nonsmooth problem instances...
- Referenced in 7 articles
- variables. A direct-search derivative-free Matlab optimizer for bound-constrained problems is described, whose ... compares favorable with that of NOMAD (Nonsmooth Optimization by Mesh Adaptive Direct Search), a well...
- Referenced in 4 articles
- CARTopt: a random search method for nonsmooth unconstrained optimization ... random search algorithm for unconstrained local nonsmooth optimization is described. The algorithm forms a partition ... phases provides an effective method for nonsmooth optimization. The sequence of iterates...
- Referenced in 4 articles
- Fortran subroutine library for nonsmooth and nonconvex optimization problems with single or multiple objective functions ... simple bounds for variables, linear, nonlinear or nonsmooth constraints, or all of them ... contain efficient codes for nonsmooth optimization...
- Referenced in 6 articles
- modern methods of global and nonsmooth continuous optimization, based on the ideas of A. Rubinov...
- Referenced in 3 articles
- margin. A novel approach based on nonsmooth optimization techniques is used. Two types of controllers...
- Referenced in 2 articles
- caused by abs(), min(), and max(). The optimization method generates successively piecewise linearizations ... embedded in the nonsmooth solver LiPsMin. Finally, minimax problems from robust optimization are considered. Numerical ... comparison of LiPsMin with other nonsmooth optimization methods are discussed...
- Referenced in 16 articles
- optimal dynamic treatment regime from data is Q-learning which involves nonsmooth operations ... data. This nonsmoothness causes standard asymptotic approaches for inference like the bootstrap or Taylor series ... confidence intervals for the parameters indexing the optimal dynamic regime. We propose an adaptive choice...
- Referenced in 1 article
- Solver-o-matic: Decision Tree for Nonsmooth Optimization Software. Solver-o-matic ... online decision tree for choosing a nonsmooth optimization solver. The tree is loosely based ... paper ”Empirical and Numerical Comparison of Several Nonsmooth Minimization Methods and Software” by N. Karmitsa ... version you can only search for unconstrained optimization solvers (although some of the solvers...
- Referenced in 12 articles
- cores). Optimization problems can be very general: functions can be noisy, nonsmooth and nonconvex, linear ... communities in mind: those who need an optimization problem solved, and those who wish...