NAG has just released their latest numerical library; the NAG Library for .NET. This is the first release of the library and includes over 400 methods for key mathematical and statistical areas, including Wavelet Transforms, Integration, Interpolation and Approximation, Random Number Generators, Time Series Analysis, and Optimization. The Optimization chapter contains methods for solving LP-, QP-, LS- and NLP-problems without constraints or with constraints. A global optimizer is also included, solving problems without constraints but with bounds on the variables.
The example in the link below illustrates how to solve a LS optimization problem using the NAG Library for .NET from F#. The problem is stated as follows: min 1/2 || b – Ax || ^ 2, where A is a (10 x 9)-matrix and b is a (10 x 1)-vector. The variables (x1,…,x9) are bounded and there are 3 general constraints.
For further questions regarding the usage of the .NET library we – the technical team at NAG (firstname.lastname@example.org) – would be happy to give anyone help using the .NET Lib for the first time or just chat…FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!