Journal ArticleDOI
Algorithm 755: ADOL-C: a package for the automatic differentiation of algorithms written in C/C++
TLDR
The C++ package ADOL-C described here facilitates the evaluation of first and higher derivatives of vector functions that are defined by computer programs written in C or C++.Abstract:
The C++ package ADOL-C described here facilitates the evaluation of first and higher derivatives of vector functions that are defined by computer programs written in C or C++. The resulting derivative evaluation routines may be called from C/C++, Fortran, or any other language that can be linked with C. The numerical values of derivative vectors are obtained free of truncation errors at a small multiple of the run-time and randomly accessed memory of the given function evaluation program. Derivative matrices are obtained by columns or rows. For solution curves defined by ordinary differential equations, special routines are provided that evaluate the Taylor coefficient vectors and their Jacobians with respect to the current state vector. The derivative calculations involve a possibly substantial (but always predictable) amount of data that are accessed strictly sequentially and are therefore automatically paged out to external files.read more
Citations
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Book
Numerical Optimization
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TL;DR: Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization, responding to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems.
Journal ArticleDOI
CasADi: a software framework for nonlinear optimization and optimal control
TL;DR: This article gives an up-to-date and accessible introduction to the CasADi framework, which has undergone numerous design improvements over the last 7 years.
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Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems
Jon C. Helton,Freddie J. Davis +1 more
TL;DR: The following techniques for uncertainty and sensitivity analysis are briefly summarized: Monte Carlo analysis, differential analysis, response surface methodology, Fourier amplitude sensitivity test, Sobol' variance decomposition, and fast probability integration.
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AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models
David A. Fournier,Hans J. Skaug,Johnoel Ancheta,James N. Ianelli,Arni Magnusson,Mark N. Maunder,Anders Nielsen,John R. Sibert +7 more
TL;DR: The basic components and the underlying philosophy of ADMB are described, with an emphasis on functionality found in no other statistical software, and the main advantages are flexibility, speed, precision, stability and built-in methods to quantify uncertainty.
Journal ArticleDOI
ACADO toolkit—An open-source framework for automatic control and dynamic optimization
TL;DR: The user‐friendly syntax of the ACADO Toolkit to set up optimization problems is illustrated with two tutorial examples: an optimal control and a parameter estimation problem.
References
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