Open source in OR: Q&A with Pyomo and HiGHS

Historian and philosopher Hannah Arendt once said, “Storytelling reveals meaning without committing the error of defining it.” While good stories of operations research and data science can come from practitioners of all kinds, this panel discussion encourages you to put your chin in your hands and elbows on the table and listen to the lessons lived and learned from a pair of industry leaders who have seen much and done much.

“I’d like help deploying this decision model. Does this .ipynb work? Or would you prefer .zip?” If you work on decision science projects, it is possible you’ve asked or been asked this question. Integrating a decision model into a live business process is a journey that necessitates applying software engineering practices to mathematical modeling in ways that are not always intuitive or straightforward. What are ways to demystify and streamline that process?

Good. Fast. Cheap. Pick two, they say. But (true to form) decision intelligence teams strive to maximize for all three — project success often hinges on it. Balancing these objectives often comes down to a team’s agility ability. What does this look like? And how is it put into practice?