Join us in welcoming Greg Hauser, OR alumnus and founder of OpenSolve, as he discusses large-scale linear optimization. Alums and friends of the program are always welcome.
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Large-Scale Linear Optimization in Practice
Linear optimization (LP/MILP) remains a popular analytical technique in industry. As computing technology has advanced, new opportunities have emerged for practitioners in implementing large-scale optimization models. In particular, cloud computing has made the scale of resources readily available to most modelers greater than ever before. A case study detailing the development and implementation of a large-scale scheduling MIP is given, along with a brief survey of proprietary and open-source software offerings available today. Best practices are reviewed for deploying modern solver software in the cloud and on-premises.
Greg Hauser graduated from NC State’s Operations Research program in 2022. His dissertation explored linear optimization theory and applications in the field of matching theory from microeconomics. He has formulated and implemented linear optimization models for the US Army, Bayer Crop Sciences, and most recently for CANA LLC. He founded OpenSolve LLC to provide an open-source software-as-a-service alternative to existing commercial solver software options. OpenSolve’s minimal-profit revenue-sharing business model is designed to keep modeler’s costs low while continuing to support open-source software development in the field of linear optimization.
