OptimJ samples installation

Ateji provides a comprehensive samples library to help you. We strongly recommend that you write your first OptimJ programs by starting from a sample and adapting it to your needs.

 

Choose sample project depending on the solver:

OptimJ works with most programming engines. Download sample project you want.

Follow this procedure to install a sample project in your workspace:

  • Copy the previous archive to your PC.
  • Open Eclipse
  • Select "File" > "Import..."
  • Select "General" > "Existing Projects into Workspace" > "Next"
  • Select "Select archive file:"
  • Set the name of the archive file.
  • Click "Finish".
  • Examples are in your workspace.

 

Content sample project

  • Basics: The issue of those examples is to show what kind of decision variables | contraints can be used with a context solver.
  • Linear problems: This projet shows a lot applications of linear problem. Moreover it shows how to write them with OptimJ and how to solve them with our favorite optimizer.
  • Diet: This is the full implementation of the example developed in whitepaper "Object-Oriented Modeling with OptimJ."
  • Quadratic problems: Quadratic problems can be solved using a quadratic optimizer.
  • Conic problems: Conic optimization can be seen as a generalization of linear optimization.
 

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Customer Quotes

 

We're going to deploy OptimJ capabilities for our ongoing Java-based projects to close a gap between optimization engines and Java applications.

Andrey Torzhkov,
Research Scientist,
Siemens Corporate Research.
Siemens

 

With OptimJ you get the expressiveness of OPL™ with the integrability and flexibility of Ilog Concert™ -- the best of both worlds.

Luc Mercier,
Phd student,
Brown University.
Brown

 

Integrating optimization projects in a Java environment becomes a breeze using the Eclipse IDE, shortening project development times up to 50%.

David Gravot,
Consulting expert in optimization,
Rostudel.

 

OptimJ made it easy to use results from different solvers and combine exact methods with metaheuristics coded in Java, for solving complex industrial problems.

Médéric Suon,
Industrial Engineer,

PSA

 

I used OptimJ to implement a model for production planning in a polystyrene factory.

Luc Mercier,
Phd student,
Brown University.
Brown

 

We've succesfully applied OptimJ to improve an existing software application developed in one of our past numerical optimization projects.

Andrey Torzhkov,
Research Scientist,
Siemens Corporate Research.
Siemens

 

Using OptimJ enabled a rapid development and integration of optimization models in Java-based applications.

Médéric Suon,
Industrial Engineer,

PSA

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