Operationalize your AMPL model and get an intro to DecisionOps in under an hour. Join us for an interactive session where you’ll deploy a decision model to scalable infrastructure to create observable, end-to-end optimization workflows.
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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.
What is HiGHS? How is it used for MIP solving? And how can you accelerate the impact of decision models that use open source projects? We’ll cover all of this with a live walkthrough, demo, and a Q&A with the HiGHS project maintainers.
In the on-demand logistics space, ML and OR are colliding more frequently with practitioners generating demand forecasts that feed into shift scheduling models that feed into vehicle routing models. How can we benefit from their combined value more often?
Learn how to use vehicle activation penalties to encourage vehicle efficiency. This is sometimes known as prioritizing backhaul when going back to a depot.
Learn how to configure your vehicle routing problem (VRP) to have multiple pickups precede a dropoff. In this example, learn how to set two pickups at two different locations precede a dropoff stop for a pickup and delivery problem.
