Princeton Optimization

Making Optimization Work in Production: Lessons from Large-Scale Applications

Following are lightly edited excerpts from Rob’s recent webinar (watch the recording here). An optimization model can perform beautifully in development but struggle or fail when it reaches production. The reason is straightforward: production changes the rules. A prototype often operates against a controlled dataset and can be given considerable time to find an answer. […]

Doing (a Lot of) Good with (Really) Good OR

At the recent INFORMS Annual Meeting, I had the great pleasure to be a judge for “Doing Good with Good OR,” https://www.informs.org/Recognizing-Excellence/INFORMS-Prizes/Doing-Good-with-Good-OR-Student-Paper-Competition, the student competition that honors projects that greatly impact society. I joined the competition committee this year and will be the co-chair with Dr. Justin Boutilier in 2023. As a global society of […]

Rapid Optimization Model Development with Python and pandas in 7 Steps

Princeton Consultants employs a 7-step methodology that improves the likelihood of success and deliverability in optimization projects. Based on our solution development and deployment for many clients in varied industries, this approach helps create useful documentation, shortens the overall development time, improves code maintainability, and provides a natural feedback loop to business requirements. The main […]