Lars Beckmann

Head of Decision Science
Lars studied computer science and specialized in operations research. He is a former MSFT employee and likes to invent things to solve problems, i.e. card games to cure boredom and a modeling language to make math models testable. He plays tennis and sings in a choir (bass).‍
Solving a fleet scheduling problem – from calculating demand to building a shift schedule

If you have a vehicle routing problem, you probably have a workforce scheduling problem, too. Here’s how we found optimized solutions to both with Nextmv’s decision automation platform.

Avoiding bridges, train tracks, and other pathways with route optimization

Unsafe roadway? Tunnel construction? Unpleasant bridge troll? We look at how to use Nextmv to optimize vehicle routes and discourage or forbid certain pathways with just a few lines of code.

Introducing ALNS to the Nextmv solving neighborhood

Find more improving solutions to route optimization problems at scale faster with ALNS, the latest solver available in the Nextmv Decision Stack.

Introducing expanders in Hop

We've released Hop v0.7.0! This release introduces a cool new feature we call expanders into Hop to help customers manage time to first feasible solution and memory use as they scale their models.

Operationalizing Java-based OR-Tools decision models

Learn how to create a decision service with your Java OR-Tools model using Nextmv. Deploy an existing model or accelerate the development of a new Java model with testing, CI/CD, and more.

Bridging the divide between optimization and production infrastructure

With Nextmv, getting a decision model into production is just like deploying any other software. Build custom models and create a unique endpoint for your model that can easily integrate into your other services.