Nextmv will be at INFORMS Annual 2024. We’re excited to see you in the land of coffee, clouds, and space needles!
Visit us at booth #222 in the exhibit area to say hello and learn more about Nextmv. We’re hosting a workshop, presenting a technology showcase, and demo-ing all the DecisionOps goodness of Nextmv. Learn more below.
When: Saturday, October 19 from 1:00 PM - 3:30 PM
Where: Summit-444 (Level 4 of Summit Building)
Accessibility: Free and open to all conference registrants
Presenter: Carolyn Mooney and Ryan O'Neil
Conceptually, the connection between machine learning (ML) and operations research (OR) is intuitive: predicting traffic patterns for delivery scheduling to consumer buying behavior for inventory management. But in practice, seamlessly blending the two disciplines can be more challenging than expected.
This interactive session will explore foundational logistics models (forecasting, scheduling, routing, etc.) alongside the tooling and techniques to link, solve, and orchestrate them for real-world, operational settings. We will demonstrate ways to employ ensembling to aggregate multiple forecasts, run multiple model scenarios, and derive consensus across model output to feed downstream applications.
Join us for an interactive session that will explore foundational logistics models, best practices for operations such as model testing and CI/CD, and tooling such as OR-Tools, Pyomo, HiGHS, Gurobi, AMPL, Statsmodels, Prophet, and more.
View on the INFORMS Annual 2024 website.
When: Monday, October 21 from 8:40 AM - 9:15 AM
Where: Room 345 of the Summit Building
Accessibility: Free and open to all conference registrants
Presenters: Carolyn Mooney and Ryan O’Neil
Optimization is founded upon the promise of efficiency and improving solutions. While it’s common to believe success starts and ends with an algorithm’s runtime, there are tremendous gains to be had beyond those bounds.
While optimization tech stack architectures and tooling development is critical, the next chapter of optimization will be defined by how teams run and operate their solution. Whether you implement a trustworthy sedan or F1 racer of optimization tech, there are key (and often overlooked) efficiencies to be realized in how teams test, tune, troubleshoot, and operate their portfolios of solutions.
As operations research and decision science teams balance the demands of budgets, headcount, revenue, timelines and success metrics, building and improving DecisionOps practices will save time, money, and headache in pursuit of optimization efficiency. This session will explore how through real-world applications and storytelling.
View on the INFORMS Annual 2024 website.
