Join the conference sponsors as they discuss innovations and best practices in the field. Descriptions and times below:
IBM
Monday, April 12, 1:45-2:25pm
Combining Machine Learning and Optimization Techniques to Address the Full Lifecycle of Data Science Problems
Presented by: Ferenc Katai, OM of CPLEX/CPO/OPL/DOC, IBM
Two use cases will be discussed how to integrate predictive/ML techniques/tools with mathematical optimization ones for the best possible business outcome.
FICO
Tuesday, April 13, 1:45-2:25pm
End-to-End FICO® Xpress Insight Tutorial: From Data to Decisions for Non-Technical Business Users
Presented by: Majid Bazrafshan
You have a team with a great analytics background. They’ve developed advanced analytical tools using Python, R, or your current optimization solver. They’ve derived crucial insights from your data and figured out how your decisions shape your customers’ behaviors. Now it’s time to put these critical analytical insights into the hands of your non-technical business users.
In this tutorial, you’ll learn how FICO’s Xpress Optimization solutions (including Xpress Mosel, Xpress Workbench, Xpress Solver and Xpress Insight) make it possible to embed your analytic models in business user-friendly applications. See how to supercharge your analytic models with simulation, optimization, reporting, what-if analysis, and agile extensibility for your ever-changing business. Plus, you’ll discover how to use the new View Designer to reduce GUI development times from minutes to seconds.
SAS
Tuesday, April 13, 2:40-3:20pm
Building and Solving Optimization Models with SAS
Presented by: Rob Pratt & Ed Hughes
SAS provides comprehensive data and analytic capabilities, including statistics, data/text mining, forecasting, and operations research methods: mathematical optimization, discrete-event simulation, and project and resource scheduling. The OPTMODEL procedure in SAS Optimization provides a powerful and intuitive algebraic optimization modeling language, with unified support for linear, mixed integer linear, quadratic, and nonlinear programming, along with constraint programming, black-box optimization, and network-oriented optimization models.
We’ll demonstrate PROC OPTMODEL, highlighting its newer capabilities—automatic linearization, indicator constraints support, and a vehicle routing problem solver. You can access these and other SAS optimization capabilities from SAS and from Python, Lua, Java, and R, thanks to the open, distributed, and cloud-enabled nature of SAS® Viya®.
XLOPTIM
Wednesday, April 14, 10-10:40am
Supply Chain Optimization Using an Excel Add-on
Presented by: Efthalia Anagnostou
Selecting the appropriate optimization solver is essential for effective supply chain management and decision making. In this talk, we will present a new powerful solver for Microsoft Excel. For this purpose, we will build a simple and intuitive model for supply optimization considering material costs as well as transport costs for each supplier.
