Carolyn Mooney

Co-Founder & CEO
Carolyn Mooney began her career running large scale ballistic missile simulations at Lockheed Martin. She adapted her skills to meal delivery in Decision Engineering at Zoomer, then led Grubhub's Systems Engineering team, consulting on projects from ETA improvements to scheduling and market management. Carolyn has a BSE in Systems Engineering from the University of Pennsylvania and coaches volleyball when she's not founding companies.‍
A 2022 Look Back and 2023 Preview

2022 was a big year: the next-gen Nextmv platform, multi-paradigm solving, INFORMS, curling in Montreal. 2023 has even more goodness in store.

Create optimized PagerDuty on-call rotation schedules with decision automation

I retired our on-call scheduling spreadsheet — and you can too. Here’s how I built a custom decision model that generates and sends optimized schedules to the PagerDuty API.

Build decision models faster with Nextmv CLI and SDK

Go from zero to working decision model in minutes — then customize or create something totally new. The new and improved Nextmv platform changes the way operational decisions get made at speed and scale.

To know your solver is to know what’s possible

Solvers help us tackle big problems. But how well do you understand the solver technology that you have? Did you build it? Buy it? Will it scale with your operations?

Nextmv + Onfleet: Partnership Announcement

It’s now easier than ever to pair Nextmv's extensible route optimization engine with Onfleet's dispatch and fleet management platform to give customers more control over automated route assignment while flexibly representing customer business logic and rules.

The what, why, and how of DecisionOps: Accelerating time to value for optimization

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.

Uncertainty, ML + OR, and stochastic optimization: Demo and Q&A with Seeker creator

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.

How to perform a scenario test for decision models

Simulate scenarios to answer "what if" questions with your decision model.

How to bring your custom Python decision model to Nextmv

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.

Getting started with DecisionOps – Live Nextmv workshop

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.

Shift scheduling algorithm comparison: Optimizing for shift coverage

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?

Order fulfillment and carrier selection experiment: Comparing handling costs

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?

Vehicle routing (VRP) algorithm test: Comparing a mixed fleet to a homogenous fleet

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.

In conversation with Ox and The Rounds: Circular logistics and human-centered automation

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.

Decision model testing for routing, assignment, order fulfillment, and shift scheduling

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.

Build decision models with confidence: Working with testing in optimization

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.

In conversation with Dr. Karla Hoffman about optimization and operations research

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.

Getting started with Nextmv

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.

From zero to customizable decision model in minutes with Nextmv

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.

Decisions as code: Systems thinking, operations research, and computer science

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.