Worldwide design engineers seeking the most appropriate way to solve difficult optimization problems intrinsic to prototyping can get easy to follow step-by-step instructions on how to select the best-suited local or global optimization routines, from the Numerical Algorithms Group (NAG) Library, by using the Decision Trees for optimization (http://www.nag.com/market/techtip027.asp).
NAG, a not-for-profit numerical software development organization, devotes R&D resources to continually advance methods for solving optimization problems and similar computational challenges. The NAG Decision Trees are part of the documentation for one of the most rigorously tested and documented sets of optimization routines and other mathematical and statistical algorithms in the world, collected into the Numerical Algorithms Group Library (http://www.nag.com/numeric/numerical_libraries.asp). The NAG Library of routines, including the optimization chapters, can be called from diverse environments such as C++, Fortran, MATLAB, and R.
Many who use NAG’s routines as the building blocks of their applications rely on the knowledge base in NAG’s documentation as a part of the “future-proofing” of their application development investments. The Decision Trees, which are a feature of this documentation, can be useful in helping new and experienced users select the appropriate routine for the problem at hand in a matter of minutes.
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