- Referenced in 41 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 77 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 36 articles
- control, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained...
- Referenced in 71 articles
- robust gradient sampling algorithm for nonsmooth, nonconvex optimization The authors describe a practical and robust...
- Referenced in 12 articles
- package ROptEst: Optimally robust estimation , Optimally robust estimation in general smoothly parameterized models using...
- Referenced in 75 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 463 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 181 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 130 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 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 87 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 47 articles
- global optimization) and the results confirm its competitiveness in terms of efficiency and robustness...
- Referenced in 9 articles
- packages for the computation of optimally robust estimators and tests as well as the necessary...
- Referenced in 212 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 4 articles
- RobLox: Optimally robust influence curves and estimators for location and scale , Functions for the determination ... optimally robust influence curves and estimators in case of normal location and/or scale...
- Referenced in 14 articles
- package for the robust and fast solution of noisy optimization problems with continuous variables varying...
- Referenced in 11 articles
- regarding the function to be optimized, it is quite robust with respect to non-quadratic ... surfaces. The degree of robustness can be adjusted by the user. In fact, simulated annealing ... used as a local optimizer for difficult functions...
- Referenced in 8 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...
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- main application concerns to a new robust optimization package with two major contributions. The first...
- Referenced in 18 articles
- offspring. Our aim is the optimization of the balance between exploration and exploitation ... robustness of this crossover, we have used a set of functions to be optimized with...