It’s new and yet old. It bridges data science and business operations. And it’s an emerging piece of critical infrastructure for realizing a more efficient, responsive, and predictable world.
A lot happened at Nextmv in 2021. Here’s a 5-minute rundown of all the goodness the team dispatched and a mini preview of what’s to come in 2022.
We love a good polyhedral representation with a side of matrix math, but we know they're not for everyone. So we're creating decision optimization tooling that allows developers to work with decisions as code.
At Nextmv, we help companies make the best decisions in the time they have. But how do you know what’s better or even good? Let’s talk about testing decisions.
It’s been two years since we started Nextmv and one heck of an exciting journey. Here’s a look at how some things have changed and how others have stayed the same.
How do optimization teams get decision models live into business processes faster as managed services? We explore this through the lens of dedicated DecisionOps workflows.
What approaches are available to decision scientists and operations researchers to incorporate more randomness and uncertainty into their models? We explore this, ML + OR, and stochastic optimization with Nextmv and Seeker.
Simulate scenarios to answer "what if" questions with your decision model.
In this step-by-step video, we’ll walk you through deploying a Python OR-Tools traveling salesperson problem (TSP) model using the Nextmv Python template.
In this hands-on workshop designed for operations researchers (decision scientists), developers, and data scientists, participants will get a guided introduction to DecisionOps via the Nextmv platform.
See how to test two shift scheduling algorithms. One algorithm increases the time between shifts to account for new labor laws compared to the other algorithm that does not. How do schedule overages change across the two?
Test two order fulfillment algorithms that consider costs for distribution center handling costs and carrier selection. A new algorithm introduces a change to account for inventory capacity at a distribution center to increase efficiency and decrease food waste. How will costs change compared to the algorithm that does not?
See how to test two VRP decision algorithms (one that has a homogenous fleet of cold chain-ready vehicles and one that is a mixed fleet with cold chain and non-cold chain vehicles) that looks to compare total time on road values and other KPIs.
The CEOs and founders of two startups sit down with Carolyn Mooney to discuss logistics and automation, navigating the evolving world of AI technology, and the benefits of efficiency and sustainability.
Four decision algorithms, multiple experiments, one platform. Explore recently released batch testing capabilities for evaluating model changes to compare output metrics, KPIs, and prepare for acceptance and scenario tests.
Optimization model testing plays a key role in ensuring smooth yet improving business operations. But the testing universe is big and sometimes unwieldy. Learn how to get started with a unified decision model testing framework.
Is optimization a solved problem? How does it fit into modern business models such as on-demand delivery? What does it mean to model like an operator? We’ll ask Dr. Hoffman these questions and more.
Build and run complete decision optimization models in minutes for vehicle routing, scheduling, packing, and Sudoku. With a few commands, you're ready to solve.
Register to watch a presentation, demo, and AMA time with the Nextmv team. Get an overview of the newly released custom decision optimization platform, see it in action, and check out a preview of our multi-solver capabilities.
From vehicle routing problems (VRPs) to scheduling staff and workers, there is a multitude of decisions ripe for automation. In this talk, Carolyn Mooney, CEO of Nextmv, talks about her vision for shifting from traditional decision workflows to decision automation where any developer can work with decisions as code.
