GANSO can be used by programs written in most common programming languages (C/C++, Fortran, ...), and packages such as Maple and Mathematica.

Global optimization is a branch of mathematics dedicated to the search for parameters providing the best outcome under given constraints. Optimizing the outcome (be it maximizing a profit, or minimizing a cost) is a very common concern in many scientific, industrial or governmental areas, and often one has to resort to mathematical modelling for these issues. When the model is linear, then several packages exist that solve the problems efficiently, but often the problems involve objective and constraints with a complex structure for which such packages are unsuitable. The GANSO library provides a set of solvers for tackling these problems.

The GANSO library provides several methods described below:

• Derivative Free Bundle Method (DFBM) of nonsmooth optimization.
  This method is a very efficient method to find local minima for problems with nondifferentiable objective functions
  
  
• Extended Cutting Angle Method (ECAM) of global Lipschitz optimization.
  This is a global solver for finding a global optimal solution to problems with multiple extrema of moderate size
  
  
• Dynamical System-based Optimization (DSO)
  This is a heuristic method for solving general global optimization problems.
  
  
• Random Start Local optimization
  
  

Each of the above methods has a different field of application. The full potential of the GANSO library is implemented through various combinations of these methods to solve problems very efficiently.

A detailed description of these methods is given in the manual and in a series of papers listed in the bibliography section of the manual. The manual describes the usage of the library GANSO in applications, including compilation, linking, description of the methods and procedures and their parameters. The manual also provides a number of example programs.

Download the GANSO Manual.