Linear Programming Library GIPALS32

Version 3.4 (January 8, 2011)

Bring Powerful Optimization Engine to Your Applications!

GIPALS32 is a linear programming library offering a simple and reliable way to solve the linear programming tasks arising in logistics, transportation, oil refinery, financial and many other practical applications to maximize profit or minimize costs.

The library can easily find a solution or state a solution doesn't exist for any kind of linear programs with an unlimited number of variables and constraints.

GIPALS32 is a Windows-based library, and it can be easily integrated into existing or new applications for Windows written on C++, Visual Basic, Visual C++, C#, Delphi and other programming languages. The library provides a simple application programming interface (API) that allows specifying or modifying the linear programming tasks using few functions and tunes the optimization engine according to user requirements.

The library doesn't require any additional DLLs or ActiveX components hence the deployment process is very simple and transparent for the users.

We understand that the integration process is most critical and difficult part of using any third-party solution. Therefore Optimalon Software provides extensive source code examples for several programming languages (C#, VB, C++, Delphi) with the trial version of CutGLib.
You can download trial version GIPALS32.ZIP on your computer, unzip and run the setup.exe and start testing our library free of charge.

You'll find all examples in "C:\Program Files\GIPALS32\Examples" or "C:\Program Files (x86)\GIPALS32\Examples" (for 64-bit Windows) folder. We also supply a precompiled executable application \Examples\Executabe\SampleExe.exe (with full Delphi source code) that you can run right way and test your own cutting examples.

The main features of GIPALS32 are:

  • Robust Interior-Point method for fast and reliable solution.
  • Unlimited number of variables and constraints.
  • Flexible preprocessing to reduce task size and optimization time.
  • Constraint matrix scaling to improve numeric stability.
  • Iterative refinement to improve solution quality and reduce the number of iterations.
  • High order Gondzio correction to improve solution quality.
  • Special method for handling dense columns constraint matrix.
  • Support the industrial standard format of linear programs.
  • Support modern high performance processors (CPU).
  • Simple programming interface.

Check the GIPALS32 Performance