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Larry Snyder headshot

Larry Snyder

Lawrence (Larry) Snyder 

Professor of Industrial and Systems Engineering and Director of the Institute for Data, Intelligent Systems, and Computation at Lehigh University

Larry Snyder is a Professor of Industrial and Systems Engineering and Director of the Institute for Data, Intelligent Systems, and Computation (I-DISC) at Lehigh University. He received his Ph.D. in industrial engineering and management sciences from Northwestern University. Dr. Snyder’s research interests include modeling and solving problems in supply chain management and energy systems, particularly when the problem exhibits significant amounts of uncertainty. His research has been published in such journals as Transportation Science, IEEE Transactions on Smart Grid, Naval Research Logistics, IIE Transactions, and Production and Operations Management and has been funded by NSF, DOE, state agencies, and several major corporations. He is co-author of the textbook Fundamentals of Supply Chain Theory, published in 2011 by Wiley, which won the IIE/Joint Publishers Book-of-the-Year Award in 2012; a second edition was published in 2019. He has delivered or co-authored over 100 presentations at academic conferences, universities, and companies. He is a founding member of Lehigh’s Integrated Networks for Electricity (INE) research cluster and Power from Oceans, Rivers, and Tides (PORT) lab. He has served on the editorial boards of Transportation Science, IISE Transactions, OMEGA, and the Wiley Series on Operations Research and Management Science.


Track: Optimization

Gamifying Learning in Mathematical Optimization

Gurobi Optimization has created an educational game that introduces new users to the power of optimization. This is a web-based app that is intended to act as an entry point for data scientists and problem solvers who would benefit from optimization; the game teaches users why optimization is valuable and important, why it’s difficult (by showcasing the scaling and added complexity of optimization throughout round play), and why solvers and other optimization algorithms are essential in finding an optimal solution.

The game is an open education tool intended to help democratize the knowledge of optimization. It is accompanied by a series of tools explaining how to teach the game in a classroom setting, how to use the game on your own, and videos introducing what’s happening in game play and the intended educational takeaways.

Gurobi created the game in collaboration with Dr. Larry Snyder of Lehigh University. The target audience of the game is data scientists, but any other problem solvers will also find the app useful and educational. We are excited to share this free educational tool with the academic and optimization communities and hope it’s a valuable resource to introduce new learners to mathematical optimization.