IBM ILOG CPLEX optimizer for linear and mixed integer programming

About IBM ILOG CPLEX Optimizer

IBM ILOG CPLEX Optimizer is designed to solve large-scale mathematical optimization problems. CPLEX solves integer programming problems, very large linear programming problems, quadratic programming problems, and has recently added support for problems with convex quadratic constraints (solved via Second-order cone programming, or SOCP).

 

Learn more about IBM ILOG CPLEX Optimizer

 

 

About OptimJ solver link for IBM ILOG CPLEX Optimizer

 

OptimJ™ for IBM ILOG CPLEX Optimizer lets you develop, debug and tune models in Java™ using state-of-the-art tools and techniques. It provides a clear and concise algebraic notation for optimization modeling, object-oriented programming for data modeling, and powerful bulk data manipulation primitives for pre- and post-processing.

 

OptimJ™ models are directly compatible with Java™ source code, existing Java libraires such as database access, Excel connection or graphical interfaces, leveraging existing code bases and training, and facilitating communication between optimization experts and IT teams.

 

OptimJ™ brings modern development tools such as Eclipse, CVS, JUnit or JavaDoc to optimization experts, improving productivity and quality.

 

You can try OptimJ™ for IBM ILOG CPLEX Optimizer with a free 30-days evaluation licence including examples of OptimJ™ models for IBM ILOG CPLEX Optimizer.

 

OptimJ™ solver link for IBM ILOG CPLEX Optimizer is reasonably priced, contact us for the details.

 

 

 

 

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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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