Quick Start

EAGO is a global optimizer primarily meant to be used with the JuMP algebraic modeling language. Typical use will involve installing EAGO and JuMP, creating a problem using JuMP syntax, and passing the problem to the EAGO optimizer.

Customization

EAGO is designed to be easily extensible. Some of the examples that follow include use cases where the standard EAGO functionality is overloaded and readily incorporated into the main optimization routine. Information on how to extend the main branch-and-bound functions (including lower and upper bounding routines) can be found in the Customization Guidelines section.

Examples

The following pages in this section include several representative examples of how EAGO can be used. Additional (and in some cases, shortened) examples can be found in the EAGO-notebooks repository. Examples and instructional pages in this section include:

• Simple Example: A base-case optimization problem solved using the EAGO optimizer. No extensions or function overloading required.
• Medium-Difficulty Example A quasiconvex optimization problem solved by overloading some of EAGO's functionality to implement a bisection-based algorithm instead of typical branch-and-bound. (TODO, but see the Jupyter Notebook version)
• Difficult/Developer Example Overloading the branch-and-bound algorithm with a custom extension type. (TODO)