Initializing help system before first use

# Mixed Integer Programming

This chapter extends the LP problem from Chapter Building models to a Mixed Integer Programming (MIP) problem. It describes how to

- transform a MIP model into matrix format,
- input MIP problems with different types of discrete variables into Xpress Optimizer,
- solve MIP problems and output the solution.

Chapter Mixed Integer Programming shows how to formulate and solve this example with Mosel, Chapter Mixed Integer Programming shows the same for Python, and in Chapter Mixed Integer Programming the same is done with Java.

Covered Topics

- Extended problem description
- MIP model 1: limiting the number of different shares
- MIP model 2: imposing a minimum investment in each share

Parent Topic Getting started with the Optimizer

© 2001-2026 Fair Isaac Corporation. All rights reserved. This documentation is the property of Fair Isaac Corporation (“FICO”). Receipt or possession of this documentation does not convey rights to disclose, reproduce, make derivative works, use, or allow others to use it except solely for internal evaluation purposes to determine whether to purchase a license to the software described in this documentation, or as otherwise set forth in a written software license agreement between you and FICO (or a FICO affiliate). Use of this documentation and the software described in it must conform strictly to the foregoing permitted uses, and no other use is permitted.