Optimization plays a key role in MatchBack Systems successfully minimizing costs and improving equipment utilization for its customers — but it's the speed to deployment and model iteration that takes their solution to the next level.
Subscribe to our newsletter.
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.
Working in Python? Stay in Python! Develop and deploy your decision model directly from your Python environment. Updates to our SDK make it even easier to operationalize custom decision models safely and quickly.
