NVIDIA/cuopt-examples

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# cuOpt Examples NVIDIA® cuOpt™ is an open-source GPU-accelerated engine for solving complex decision optimization problems, such as Mixed Integer Programming, Linear Programming, and Vehicle Routing problems. This repository contains a collection of examples demonstrating the use of NVIDIA cuOpt via service APIs, SDK, and Integration with other OSS optimization packages. This repository is under [Apache 2.0 License](LICENSE.md) [cuOpt Docs](https://docs.nvidia.com/cuopt/) ## Quick Start with Docker The easiest way to get started with these examples is using cuOpt docker image. ### Prerequisites - [Docker](https://docs.nvidia.com/ai-enterprise/deployment/vmware/latest/docker.html) - [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-the-nvidia-container-toolkit) - NVIDIA GPU with appropriate drivers ## Requirements For detailed system requirements, please refer to the [NVIDIA cuOpt System Requirements documentation](https://docs.nvidia.com/cuopt/user-guide/latest/system-requirements.html#). Specific requirements are listed in each workflow's README.md and in the root directory's requirements.txt files. ### Running the Examples 1. Clone this repository: ```bash git clone https://github.com/NVIDIA/cuopt-examples.git cd cuopt-examples ``` 2. Pull the cuOpt docker image: For cuda-13: ```bash docker pull nvidia/cuopt:latest-cu13 # To pin to a specific release: docker pull nvidia/cuopt:26.8.0-cu13 ``` For cuda-12: ```bash docker pull nvidia/cuopt:latest-cu12 # To pin to a specific release: docker pull nvidia/cuopt:26.8.0-cu12 ``` 3. Run the examples: For cuda-13: ```bash docker run -it --rm --gpus all --network=host -v $(pwd):/workspace -w /workspace nvidia/cuopt:latest-cu13 /bin/bash -c "pip install -r requirements.txt; jupyter-notebook" ``` For cuda-12: ```bash docker run -it --rm --gpus all --network=host -v $(pwd):/workspace -w /workspace nvidia/cuopt:latest-cu12 /bin/bash -c "pip install -r requirements.txt; jupyter-notebook" ``` 4. Open your browser with the link provided in the terminal, and you can see the notebooks. ## Note These notebooks have been tested on [NVIDIA Launchable](https://brev.nvidia.com/launchable/deploy?launchableID=env-2qIG6yjGKDtdMSjXHcuZX12mDNJ), [Google Colab](https://colab.research.google.com/github/NVIDIA/cuopt-examples/blob/cuopt_examples_launcher/cuopt_examples_launcher.ipynb), and local Jupyter environments. They may work on other platforms as well. ## Repository Structure The repository is organized by use cases, with each directory containing examples and implementations specific to that use case. Each use case directory includes: - Example notebooks - README.md with specific instructions ## Featured Examples ### Intra-Factory Transport Optimization The `intra-factory_transport` directory contains an example of using the cuOpt SDK API to solve a Capacitated Pickup and Delivery Problem with Time Windows (CPDPTW) for optimizing routes of Autonomous Mobile Robots (AMRs) within a factory environment. ## Contributing We welcome contributions! Please see our [CONTRIBUTING.md](CONTRIBUTING.md) file for guidelines on how to contribute new examples or improve existing ones. ## Tutorial Videos [Example videos](https://docs.nvidia.com/cuopt/user-guide/latest/resources.html#cuopt-examples-and-tutorials-videos) can be found listed in the documentation

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cuopt-model-mapper

数据科学家

Map interpreted optimization problems into cuOpt-native models for the fast path with minimal clarifying questions.

原文语言：英语

2026-07-29

cuopt-sandbox

数据科学家

Run cuOpt in the NemoClaw sandbox — probe/smoke gates, prefer cancelable Python gRPC jobs, use legacy remote execution only when that API is unavailable, then vendored cuOpt skills.

原文语言：英语

2026-07-29

optimization-mode-router

数据科学家

Choose fast direct-to-cuOpt solve versus replayable or auditable model artifact mode.

原文语言：英语

2026-07-29

tabular-optimization-ingestion

数据科学家

Infer optimization structure from uploaded tables and identify minimal clarifications before cuOpt modeling.

原文语言：英语

2026-07-29

cuopt-debugging

软件开发工程师

Troubleshoot cuOpt LP/MILP problems including errors, wrong results, infeasible solutions, performance issues, and status codes. Use when the user says something isn't working, gets unexpected results, or needs help diagnosing issues.

原文语言：英语

2026-07-20

optimization-from-data-orchestrator

软件开发工程师

Coordinate uploaded data plus a natural-language question into interpretation, clarification, cuOpt solve, and a user-facing answer.

原文语言：英语

2026-06-24

optimization-intent-router

软件开发工程师

Classify whether a data-backed request is LP, MILP, QP, routing, or non-optimization analytics.

原文语言：英语

2026-06-24

generic-max-supply

软件开发工程师

Multi-period supply chain planning model: data files, BOM structure, variable/constraint reference for the max-supply base model.

原文语言：英语

2026-03-12

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