Discovering CPLEX Optimization Studio

Provides an overview of CPLEX® Optimization Studio, introduces OPL and scripting, and the IDE. Also introduces the optimization engines CPLEX Optimizer and CP Optimizer.

The main reason for using CPLEX Optimization Studio is to simplify and speed up the development and deployment of optimization-based applications. There are two kinds of people involved in the development of these applications: optimization experts, who are trained in operations research and know about mathematical modeling, and software developers, who are responsible for the data interfaces and the user interfaces that are needed to develop an optimization-based decision support application.

OPL, the modeling language, allows you to write a mathematical representation of your problem that is separate from your data. In OPL, a project is defined as one or more model files and one or more data files. Within a project, a run configuration represents a problem instance with a model and a data file, and you can have multiple run configurations within an OPL project.

There are two optimization engines. The mathematical programming optimization engine is called the CPLEX Optimizer and implements the Simplex method, the Barrier method and Mixed Integer programming. The constraint programming engine is called CPLEX CP Optimizer. This is another technology for optimization that is built on artificial intelligence principles. Constraint programming and mathematical programming are often complementary, since the strengths of one complement the weaknesses of the other.

The following documents will enable you to discover CPLEX Optimization Studio.

  • Introduction to IBM ILOG CPLEX Optimization Studio

    Provides an overview of CPLEX Optimization Studio.

  • Introduction to OPL

    Gives a short tour of the OPL modeling language, discusses some modeling issues, and illustrates optimization modeling with two examples.

  • Introduction to scripting

    The OPL language covers the requirements for expressing constraints on decision variables. However, an optimization application might also need functionality for manipulating data. This "non-modeling" expressiveness of OPL is called scripting, and is available as IBM ILOG Script. It is used to combine OPL models and interact with them. IBM ILOG Script is an implementation of JavaScript.

  • Getting Started with the IDE

    Contains an introduction to the IDE, and a tutorial that explains how to create an empty project, enter an OPL model, add data and a settings file, create run configurations and execute the final project.

  • Parameters and Settings in OPL

    Presents the parameters and options that you can set in the OPL settings (.ops) file, via the settings editor in the IDE. The command to create a settings file is File > New > Settings. You can control the type of optimization you want by modifying the values of the parameters, which are the settings for the optimization engines.

  • Getting Started with CPLEX

    Introduces the components of CPLEX, describes how to set up CPLEX for your particular platform or IDE, and offers tutorials for the components of CPLEX, including the Interactive Optimizer and the application programming interfaces.

  • Getting Started with CP Optimizer

    Provides an overview of CP Optimizer. Contains tutorials that guide you in learning about the concepts and features of CP Optimizer. As you follow the steps in the tutorial, you complete the OPL code and learn about the concepts. Then you compile and run the code and analyze the results. At the end of each tutorial, there are review exercises.

Where to find the examples

On Windows platforms, the default installation directories are:

C:\Program Files\IBM\ILOG\CPLEX_Studio<version>\opl\examples\opl

C:\Program Files\IBM\ILOG\CPLEX_Studio<version>\cplex\examples

C:\Program Files\IBM\ILOG\CPLEX_Studio<version>\cpoptimizer\examples