Introduction

Building on the introductory Guide for evaluators this document provides a framework for evaluating advanced optimization tasks with FICO^® Xpress Optimization. In particular, this guide shows you how to:

1. Parameterize and tune optimization algorithms.
2. Interact with the solvers through callback functions.
3. Obtain multiple solutions.
4. Analyze and handle infeasibility.
5. Exchange data in memory.
6. Work on a distributed architecture.
7. Control the remote execution of Mosel models without any local Xpress installation.

All examples in this guide are provided as Xpress Mosel models (Evaluation Scenario 1). Where applicable, we also explain how to perform the same tasks with Xpress BCL (Evaluation Scenario 2) or the Xpress Optimizer (Evaluation Scenarios 3 or 4, examples are provided for the Optimizer libraries, the Optimizer command line, or the Xpress Python interface).

Please refer to the Guide for evaluators for any questions relating to the installation of Xpress or recommendations for the choice of products from FICO Xpress Optimization.