- Referenced in 62 articles
- needed to perform the optimization. These function evaluations can be linear or nonlinear functions ... linear structural finite element simulation. Very little formal knowledge of optimization techniques is needed ... handle constrained, unconstrained, linear and non-linear optimization problems and can automatically calculate finite difference...
- Referenced in 1033 articles
- free MATLAB toolbox for rapid prototyping of optimization problems. The package initially aimed ... significantly. YALMIP 3 can be used for linear programming, quadratic programming, second order cone programming...
- Referenced in 120 articles
- derivative-free methods for numerical optimization of non-linear or non-convex continuous optimization problems...
- Referenced in 196 articles
- KNITRO is a solver for nonlinear optimization. It is the most powerful and versatile solver ... effective for solving linear, quadratic, and nonlinear smooth optimization problems, both convex and nonconvex...
- Referenced in 63 articles
- Riccati Equations, Model Reduction Problems, and Linear–Quadratic Optimal Control Problems Users ’ Guide (Version ... solution of large Riccati equations and linear-quadratic optimal control problems...
- Referenced in 107 articles
- Implementing interior point linear programming methods in the Optimization Subroutine Library. This paper discusses ... barrier) methods for linear programming within the framework of the IBM Optimization Subroutine Library. This...
- Referenced in 543 articles
- have proved highly effective for solving constrained optimization problems with smooth nonlinear functions ... consider problems with general inequality constraints (linear and nonlinear). We assume that first derivatives ... important application is to trajectory optimization in the aerospace industry. Numerical results are given...
- Referenced in 322 articles
- optimization, probability, financial economics and optimal control, can be viewed as particular instances ... linear matrix inequality (LMI) relaxations of the GPM, whose associated monotone sequence of optimal values...
- Referenced in 319 articles
- Linear, Nonlinear (convex & nonconvex/Global), Quadratic, Quadratically Constrained, Second Order Cone, Stochastic, and Integer optimization models...
- Referenced in 146 articles
- solving optimal control problems. Applications include trajectory optimization, chemical process control and machine tool path ... sparse linear algebra technology to solve very large optimization problems orders of magnitude faster than...
- Referenced in 71 articles
- Fortran subroutines for doing numerical linear algebra and optimization. It may be used to solve...
- Referenced in 228 articles
- functions—from linear to trigonometric—promoting deep understanding. Sketchpad is the optimal tool for interactive...
- Referenced in 30 articles
- TOMLAB OPERA toolbox for linear and discrete optimization. The Matlab toolbox OPERA ... Matlab mfiles, which solves basic linear and discrete optimization problems in operations research and mathematical ... programming. Included are routines for linear programming (LP), network programming (NP), integer programming ... Matlab for research and teaching in optimization. Linear programs are solved either by direct call...
- Referenced in 175 articles
- simpler optimization problem, which has a quadratic objective and linear constraints. This QP is still ... evaluation of the functions defining the nonlinear optimization problem, and their derivatives, is time consuming...
- Referenced in 24 articles
- package Rsolnp: General Non-linear Optimization. General Non-linear Optimization Using Augmented Lagrange Multiplier Method...
- Referenced in 35 articles
- Maximum Likelihood (ML) estimation and non-linear optimization, and related tools. It includes a unified...
- Referenced in 75 articles
- Fortran subroutines for nondifferentiable optimization with simple bounds and general linear constraints. Subroutine PMIN, intended...
- Referenced in 64 articles
- efficient extreme points of a multiple objective linear program is described. To create MOLP test ... easier to find good near- optimal solutions with linear utility functions than with, for instance...
- Referenced in 19 articles
- Evolino: hybrid neuroevolution / optimal linear search for sequence learning. Current Neural Network learning algorithms ... regression or quadratic programming to compute optimal linear mappings from hidden state to output. Using...
- Referenced in 30 articles
- abstracts many problems in numerical linear algebra, optimization, and other areas of data science ... weaker than those in comparable work. Linear convergence is obtained under suitable assumptions. We propose ... special cases of ARock for linear systems, convex optimization, and machine learning, as well...