- Referenced in 92 articles
- Robust optimization made easy with ROME We introduce ROME, an algebraic modeling toolbox ... class of robust optimization problems. ROME serves as an intermediate layer between the modeler ... solver engines, allowing modelers to express robust optimization problems in a mathematically meaningful ... modeling and subsequent numerical analysis of robust optimization problems. ROME is freely distributed for academic...
- Referenced in 61 articles
- control, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained...
- Referenced in 89 articles
- problems. The TOMLAB optimization environment is flexible, easy-to-use, robust and reliable ... applied optimization problems. TOMLAB has grown out of a need for advanced, robust and reliable ... software for the solution of applied optimization problems. TOMLAB supplies Matlab solver algorithms, as well...
- Referenced in 106 articles
- robust gradient sampling algorithm for nonsmooth, nonconvex optimization The authors describe a practical and robust...
- Referenced in 126 articles
- characteristics of optimization problems. It is thus helpful to improve the robustness of the algorithm ... adaptive DE algorithms, the canonical particle swarm optimization, and other evolutionary algorithms from the literature...
- Referenced in 15 articles
- package ROptEst: Optimally robust estimation , Optimally robust estimation in general smoothly parameterized models using...
- Referenced in 625 articles
- allows for robust and repeatable experiments: robust because performance results with artificially-generated matrices ... that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical...
- Referenced in 13 articles
- equation model by maximum likelihood and optimal B-robust methods. A stacked ascii file ... models. This paper presents a class of robust estimators for linear and non-linear simultaneous ... observations, and to some model misspecifications. An optimality principle ... leads to the construction of an optimal robust estimator which is the best trade...
- Referenced in 237 articles
- deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which -- despite ... algorithms have applications in signal processing, optimization and LSI information retrieval...
- Referenced in 178 articles
- solving linear, quadratic, and nonlinear smooth optimization problems, both convex and nonconvex. It is also ... MINLP). KNITRO is highly regarded for its robustness and efficiency. KNITRO provides a wide range ... KNITRO will remain the leader in nonlinear optimization...
- Referenced in 124 articles
- those by the much more expensive global optimization method on the same generalized block Krylov ... method show that our method is more robust and converges almost two times faster...
- Referenced in 62 articles
- global optimization) and the results confirm its competitiveness in terms of efficiency and robustness...
- Referenced in 5 articles
- Algorithms and concepts for robust optimization. In this work we consider uncertain optimizition problems where ... RecFeas and RecOpt to such a robust optimization problem, using a location theoretic point ... continuous and discrete problem applications of robust optimization: Linear programs from the Netlib benchmark ... library ROPI as a framework for robust optimization with support for most established mixed-integer...
- Referenced in 9 articles
- packages for the computation of optimally robust estimators and tests as well as the necessary...
- Referenced in 6 articles
- package RobLox: Optimally robust influence curves and estimators for location and scale , Functions ... determination of optimally robust influence curves and estimators in case of normal location and/or scale...
- Referenced in 8 articles
- main application concerns to a new robust optimization package with two major contributions. The first...
- Referenced in 269 articles
- international reputation as a source of robust and efficient numerical software. Among its best known ... processors. If you are interested in our optimization or nonlinear equation solving packages, our work...
- Referenced in 17 articles
- genetic algorithm based approach that is robust but computationally intensive for maximizing the likelihood. This ... gradient based optimization algorithm yield optimization that is robust and typically faster than the genetic...
- Referenced in 5 articles
- KAdaptabilitySolver: k-adaptability-solver is a numerical optimization package, written in C++, for solving ... counterparts of two-stage mixed-integer robust optimization problems, based on our paper K-Adaptability ... Stage Mixed-Integer Robust Optimization, Mathematical Programming Computation...
- Referenced in 20 articles
- package for the robust and fast solution of noisy optimization problems with continuous variables varying...