Haversine vs. OSRM: Distance and cost experiments on a vehicle routing problem (VRP)

How do you test if you should use map data over Haversine for a vehicle routing problem? Let’s use batch experiments with Nextmv to find out!

The Nextmv AMPL integration: Accelerating decision model development with DecisionOps

Do you model optimization problems with AMPL? The Nextmv AMPL integration accelerates how you run, test, and deploy AMPL decision models using DecisionOps tooling and workflows.

Nextmv Gurobi integration: Build, test, deploy decision models using Gurobi and DecisionOps

Do you solve decision science problems with Gurobi? The Nextmv Gurobi integration accelerates how you run, test, and deploy decision models running Gurobi with Nexmv’s DecisionOps platform.

Nextmv Pyomo integration: Build, test, deploy Python-based decision models faster

Do you model optimization problems with Python and Pyomo? The Nextmv Pyomo integration makes it easier than ever to run, test, and deploy Pyomo models using Nexmv’s DecisionOps platform.

To change my decision model, or not? That’s not a question. It’s a test.

Change can be scary or energizing. But when it comes to developing and deploying algorithms that make routing, scheduling, and fulfillment decisions, ready-made testing tools tilt the balance in favor of energizing by building confidence.

Optimization modeling with AMPL, Streamlit, and Nextmv: A stochastic facility location example

Create robust and interactive decision apps with AMPL as the optimization layer, Nextmv as the DecisionOps layer, and Streamlit as the UI and visualization layer. Learn how with a facility location example.

Getting started with DecisionOps for decision science models using Gurobi

Learn how to accelerate development of decision models that use Gurobi with tools for historical and online testing, run history, model management, and model collaboration.

Nextmv Gurobi integration speedrun demo

See how the Nextmv Gurobi integration works in the Nextmv platform. With a few commands, you can apply DecisionOps to your decision modeling workflow to build, test, and deploy faster.

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.

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?

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.

Several people are optimizing: Collaborative workflows for decision model operations

The next era of optimization isn't about building a better solver. It's about collaborative, opinionated tooling that empowers teams to move faster with less confusion and more access to the decision technology ecosystem.

Solve a route optimization problem (VRP / CVRP) with Go and Nextmv Cloud

Get started with Nextmv Cloud and Go to solve a vehicle routing problem and find optimized solutions for your vehicles and stops.

Solve a route optimization problem (VRP / CVRP) with Python and Nextmv Cloud

Get started with Nextmv Cloud and Python to solve a vehicle routing problem and find optimized solutions for your vehicles and stops.

Roadmap preview: Integrations, scenario planning, and custom decision automation

Join our team for a techtalk video as they dive into the latest routing optimization features and chat about what’s coming soon to Nextmv in the decision automation space.

Nextmv Onfleet Integration Demo

Get started with the Nextmv Onfleet integration in a step-by-step walkthrough for how to pull in tasks and workers via the Onfleet API, find optimized routes with Nextmv with extended features, and upload assignments back into Onfleet's platform.

Tour of Nextmv Cloud

Welcome to a tour of the Nextmv Cloud console! Learn how to get started with sample files for your routing use case. Optimize routes for delivery, distribution, and sourcing with Nextmv.Get started with Nextmv Cloud with our documentation.

Using the precedes and succeeds constraints for stop sequencing

When performing route optimization for use cases like delivery, distribution, and sourcing, the order in which the stops are serviced is critical. Learn how to use precedence to ensure your stops are visited in the correct sequence.

Using route limits to regulate operational costs during route optimization

Balance vehicle usage by using constraints on aspects of route to limit maximum distance traveled, maximum time spent on route, and/or maximum number of stop serviced.