Testing optimization models improves workflows, increases stakeholder buy-in, and helps teams deploy to production safely and quickly. But what are the steps to make testing repeatable and scalable?
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Do you launch decision model A or B? What happens if an operator makes a manual override? How does a new optimization model perform against real-world data? Testing and experimentation has the answers, but getting them has traditionally been a challenge.
Create a release process for your custom model that mirrors your experience for shipping any other software. Develop locally, deploy to operational environments, test performance, use version control for easy rollbacks, and iterate with confidence.
We built a docs site that references code samples from external files to avoid copy-paste errors, makes it easier to manage code updates over time, and allows for separate testing processes to be run to validate referenced code. Here’s how.
This post explains what order fulfillment is, considerations for model constraints and objective functions, and walks you through building a custom optimization model, step by step.
New views in the Nextmv console show the run history and run details for decision apps on Nextmv Cloud. Enhance development workflows, simplify collaboration, and improve KPIs.
