Operationalizing Python-based Pyomo MIP decision models

Learn how to build, test, and deploy Pyomo mathematical optimization models faster with Nextmv, featuring pre-bundled solvers for CBC and GLPK. Create a new model or integrate an existing one to accelerate its development with DecisionOps.

In this techtalk, you’ll see how to start with the Nextmv Pyomo integration to build a shift scheduling MIP model in Python, use GitHub Actions to automate deployment, and perform experiments to rollout to production confidently. 

Key topics

  • Deploy your Python-based Pyomo model to remote infrastructure in minutes
  • Use Git flows, CI/CD, and version control to iterate and improve decision models 
  • Perform experiments like acceptance tests to de-risk production rollout. 

You can try out the sample workflow demoed in this video by visiting the community apps repo and creating a free Nextmv account. If you have questions, feel free to contact us.