Create and manage queues directly in Nextmv to easily prioritize model runs. Configure prioritization at runtime to prevent blocking the queue with large runs or at the model version level to ensure production runs have precedence.
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2024 was the year of the Python modeling experience, optimization integrations, and helping modelers find solutions even faster with parallel runs and interactive visualizations. In 2025, we look forward to combining ML & OR, more data integrations, and decision pipelines for smoother operations.
Increasingly, OR practitioners are seeking to incorporate more real-world uncertainty into decision models instead of only relying on deterministic optimization approaches. In this interview, we’ll explore this topic through the lens of Seeker, a new stochastic optimization solver.
Whether you’ve already built a decision model or are just getting started, developing your optimization project on the Nextmv platform will give you the framework, testing tools, and ease of integration required to prove the value of your decision model.
Looking to innovate in operations research? Or better translate academic research to industrial practice? Build or practice modeling skills set up for real-world impact? Check out this starter guide to hosting challenges on Nextmv.
Decision models are sophisticated algorithms that power revenue, sustainability, and efficiency goals through optimized planning. But integrating them into software stacks is not always straightforward.
