DSC Webinar Series: Mathematical Optimization Modeling: Learn the Basics

Mathematical optimization (MO) technologies are being utilized today by leading global companies across industries – including aviation, energy, finance, logistics, telecommunications, manufacturing, media, and many more – to solve a wide range of complex, real-world problems, make optimal, data-driven decisions, and achieve greater operational efficiency. An increasing number of data scientists are adding MO into their analytics toolbox and developing applications that combine MO and machine learning (ML) technologies. In this series of webinars, we will show you how – with MO techniques – you can build interpretable models to tackle your prediction and classification problems.

In this latest Data Science Central webinar, you will learn:

The main components of an MO problem.
How to formulate an MO model.
How to build an MO model using the Gurobi Python API.
How to modify the original model formulation to accommodate changing conditions.
How to implement changes in the model using the Gurobi Python API.

Pano Santos, Senior PhD, Senior Technical Manager - Gurobi Optimization

Hosted by:
Sean Welch, Host and Producer - Data Science Central

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Comment by Samuel Tosin Lawal on March 12, 2020 at 12:18am

Mathematical optimisation techniques can be used to solve many business problems where resource allocation and decision making is needed to be done by an organisation The method is used by many organisation to make optimal resource  allocations.

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