OptimJ solver link for Gurobi |
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Gurobi™ 1.0 is a new generation MIP solver that leverages the computing power of multi-core processors.
The Gurobi suite of optimization products represent completely new implementations, redesigned from the ground up to fully exploit the latest mathematical and engineering improvements in the underlying methodologies, as well as developments in modern desktop computing hardware and programming environments. OptimJ™ for Gurobi lets you develop, debug and tune models in a modern modeling language 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. Try OptimJ for GurobiTry OptimJ with a free 30-days evaluation licence and download examples of OptimJ models for the Gurobi solver. |
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.
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.
Integrating optimization projects in a Java environment becomes a breeze using the Eclipse IDE, shortening project development times up to 50%.
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,
I used OptimJ to implement a model for production planning in a polystyrene factory.
Luc Mercier,
Phd student,
Brown University.
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.
Using OptimJ enabled a rapid development and integration of optimization models in Java-based applications.
Médéric Suon,
Industrial Engineer,