cuOpt for Supply Chain - Optimization scenarios supported

Hello Team,

We are planning a product focused on
Supply Chain planning and modeling. Nvidia cuOpt seems to be a class apart for the Vehicle Routing Problem. We came across the following blog article and the embedded video where there is a mention of cuOpt solver being applied to LP problems beyond VRP
Ref: https://developer.nvidia.com/blog/building-an-ai-agent-for-supply-chain-optimization-with-nvidia-nim-and-cuopt/

In addition to the well-known vehicle routing problem (VRP), cuOpt can optimize for linearly constrained problems on the GPU, expanding the set of problems that cuOpt can solve in near-real time.

The solution offers end-to-end visibility, demand forecasting methods, auto-fulfillment optimization, dynamic planning optimization, and integrated business planning in near-real time.

The scenario illustrated in the video also shows a stock allocation problem in the context of dynamic supply and demand constraints.
We wanted to know if these are in fact supported today. Or are these capabilities being worked on and not GA yet? If these are supported, it would be a great help if you could share more documentation on these capabilities.

Thanks in advance
Sriram

Team, any comments or additional information would help!
Thanks

Hi Sriram10,

Thank you for your interest in cuOpt. There are a couple of different phases:

  1. VRP Solver - this supports any variants of routing (CVRP, CVRPTW, PDPTW, TSP). It is available today for trial and license via NVIDIA AI Enterprise. You can also get started on it by accessing the API catalog - NVIDIA NIM | nvidia-cuopt.
  2. LP/MIP solver - This was available as beta access in a limited capacity. It will be offered as Open Early Access in Spring 2025. Even related documentation will be available at the same time.

Let us know if there us anything else we can help.

Regards,
cuOpt Team

2 Likes

Thank you @preethim
We will be looking forward to the other LP/MIP services in the context of supply chain.

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