Resource Management Optimization Demo

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This demo considers the problem of identifying labor resources that “best” match the requirements
of specific jobs. There are two aspects that make this problem difficult:

1. How to quantify the concept of a “good“ match?
2. How to explore an astronomically large solution space to identify the best assignment of resources to jobs?

The main components of the solution approach used in this demo are:

■ A Machine Learning (ML) model that estimates how well a resource profile (resume) matches job requirements. Specifically, the ML model computes a matching score for all resource and job combinations that estimates the quality of the match.
■ A Mixed Integer Programming (MIP) model that tackles the combinatorial
complexity of the problem, producing optimal or near-optimal assignments.

To access the cutting stock demo you will need:

• Then login to the Gurobi website

Presented by: Pano Santos, Sr. Technical Content Manager at Gurobi.

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