- Referenced in 43 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 40 articles
- control, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained...
- Referenced in 79 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 72 articles
- robust gradient sampling algorithm for nonsmooth, nonconvex optimization The authors describe a practical and robust...
- Referenced in 85 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...
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- package ROptEst: Optimally robust estimation , Optimally robust estimation in general smoothly parameterized models using...
- Referenced in 486 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 184 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 138 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 50 articles
- global optimization) and the results confirm its competitiveness in terms of efficiency and robustness...
- Referenced in 92 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...
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- 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...
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- 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 216 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 15 articles
- package for the robust and fast solution of noisy optimization problems with continuous variables varying...
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- 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 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...
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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...