Knitro: An Integrated Package for Nonlinear Optimization

By Richard H. Byrd, Jorge Nocedal, Richard A. Waltz. 2006

1,185 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Numerical Analysis

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Citations in the corpus

Learning Optimized Risk Scores (2016, methodology): “[18] Byrd, Richard H, Jorge Nocedal, and Richard A Waltz.”
An interior penalty method for optimal control problems with state and input constraints of nonlinear systems (2016, methodology): “KNITRO: An Integrated Package for Nonlinear Optimization.”
Benchmarking optimization solvers for structural topology optimization (2015, methodology): “This includes those implemented in the KNITRO package (Byrd et al. 2006), the interior point method in LOQO (Vanderbei 2006), the sequential augmented Lagrangian algorithms in LANCELOT (Conn et al.”
Algorithm 902: GPOPS, A MATLAB software for solving multiple-phase optimal control problems using the gauss pseudospectral method (2010, methodology): “The NLP is then solved using one of a variety of well-known software packages [Gill et al. 2002; Byrd et al. 2006; Betts and Frank 1994].”
Improving the Numerical Performance of Static and Dynamic Aggregate Discrete Choice Random Coefficients Demand Estimation by Jean-pierre Dubé, (2012, methodology): “We use the TOMLAB interface to call the KNITRO optimization package (Byrd, Hribar, and Nocedal (1999), Byrd, Nocedal, and Waltz (2006)) in MATLAB.9 We compare three implementations of the NFP algorithm, each initialized with the same starting values.”
An Optimal Control Approach to Sequential Machine Teaching (2018, result): “We also tried Knitro, a state-of-the-art commercial solver (Byrd et al., 2006), and it produced similar results.”
A General-Purpose Software Framework for Dynamic Optimization (Een algemene softwareomgeving voor dynamische optimalisatie) (2013, methodology): “AD Algorithmic differentiation BDF Backward differentiation formulas CCS Compressed column storage CPU Central processing unit CRS Compressed row storage DAE Differential-algebraic equation END External numerical differentiation GN Gauss-Newton GPU Graphics processing unit IND Internal numerical dif”
( Preprint ) AAS 09-334 A SURVEY OF NUMERICAL METHODS FOR OPTIMAL CONTROL (2009, methodology): “In order to implement simultaneous simulation, the discretiz ed dynamics are written as defect constraints of the form ζj = Ẋ(τj) − f(x(τj), τj) (26) The defect constraints can then be stacked into a matrix as”
Algorithms and Software for Convex Mixed Integer Nonlinear Programs (2012, background): “Combining both integrality and nonlinearity can lead to examples of MINLP that are undecidable [68].”
Interior Point Methods for Nonlinear Optimization (2010, neutral): “org/Ipopt KNITRO [14], http://www.”
Imposing Radiality Constraints in Distribution System Optimization Problems (2012, methodology): “The DSR and DSP problems were solved using a nonlinear B&B algorithm based on [29] and coded in AMPL language, while the nonlinear programming (NLP) problems were solved through the commercial solver KNITRO [30].”
Complementarity Formulations of ' 0 -norm Optimization Problems (2013, background): “For this purpose, the MILP60 option reports the best incumbent obtained in one minute, equivalent to about 2.5 minutes of CPU time.”
A review and comparison of solvers for convex MINLP (2018, methodology): “Surprisingly, both BONMIN-BB, Knitro, and Minotaur-BB performed better, with respect to the other solvers, on the set of problems with a high discrete density.”
General Heuristics for Nonconvex Quadratically Constrained Quadratic Programming (2017, background): “O15], CPLEX [IBM13], MOSEK [ApS17], and SCIP [Ach09]provide globalmethods formixed-integer nonlinearprograms, with limited support for nonconvex constraints. Packages such as ANTIGONE [MF14a], KNITRO [BNW06], and NLopt [Joh14] provide global and local optimization methods for nonlinear optimization ”