This dataset is a simulated, experimental, and fictitious representation of a supply chain company. We created this dataset to advance research and development in the fields of operations research, supply chain management, and business management. The dataset, representing various aspects of a hypothetical supply chain company (Opti Coffee), offers a rich and diverse resource for testing, analyzing, and improving supply chain models. It is divided into production data, public relations materials, internal documents, optimization solver codes, and visualization tools, reflecting the multifaceted nature of real-world business operations. This fictional dataset provides a platform for researchers and practitioners to freely experiment with and validate their models and strategies, free from the constraints and sensitivities of real-world data.

All data related to the company are located in the opti_coffee folder, which is classified into the following subfolders:

• opti_coffee/database: CSV data realted to the company's production.
• opti_coffee/public: Public relations files and documents of the company.
• opti_coffee/internal: Internal documents of the company.
• opti_coffee/solver: Code related to the supply chain optimization solver, featuring mixed integer programming (MIP).
• opti_coffee/visualization: Code for visualizing some properties of the company.

If you find this repository useful, please cite the following paper:

@article{li2023large,
  title={Large Language Models for Supply Chain Optimization},
  author={Li, Beibin and Mellou, Konstantina and Zhang, Bo and Pathuri, Jeevan and Menache, Ishai},
  journal={arXiv preprint arXiv:2307.03875},
  year={2023}
}

Please note that all data contained within the Opti Coffee Roasting Company Dataset is entirely fictitious and has been created for experimental and educational purposes only. The dataset is a simulated representation and does not reflect any real-world data or scenarios. It is designed to provide a sandbox environment for research in operations research, supply chain management, and business management.

Some data in this repository were partially generated by ChatGPT and GPT from OpenAI and Microsoft Azure, and please be mindful of the following terms of use from these organizations.

• No Real-World Accuracy: The data should not be used as a reference for real-world business practices, strategies, or decisions.
• Educational Use: The primary purpose of this dataset is to serve as a learning tool for students, researchers, and practitioners in related fields.
• No Confidential Information: The dataset does not contain and is not based on any confidential, proprietary, or sensitive information.
• Compliance with OpenAI's Policy: In alignment with OpenAI's policies, particularly regarding the use of data generated by GPT models, we adhere to specific guidelines to ensure ethical and responsible utilization of such data. OpenAI emphasizes responsible AI practices, especially in the generation and use of synthetic data created by models like GPT.

By using this dataset, you acknowledge and agree that any resemblance to actual events, locales, or persons, living or dead, is purely coincidental. This dataset should not be used for any commercial purposes or to train machine learning models.

This project is under the MIT license. We welcome contributions and suggestions! If you're interested in contributing, here are some guidelines to get you started:

1. Submitting Changes: Please submit a pull request with a clear description of the changes and the benefits they bring to the project. Ensure that your code adheres to the existing coding style and structure.
2. Reporting Issues: If you find any issues or have suggestions for improvements, please create an issue in the GitHub repository. Be as detailed as possible in your description to help us understand your concern or suggestion.
3. Data Contributions: If you wish to contribute additional simulated data, ensure that it aligns with the theme and structure of the existing dataset. Data should be fictional and not contain any sensitive or real-world information.
4. Code Contributions: Contributions to the solver and visualization tools are welcome. Whether it's optimization, bug fixes, or new features, we value your expertise and input.

Thank you for considering contributing to our project. Your efforts help make this resource more valuable for everyone.

You are free to use the Opti Coffee Roasting Company Dataset for educational, research, and evaluation purposes. However, we ask that you refrain from using it for training machine learning or statistical models. This restriction is crucial for several reasons:

1. Fictitious Nature of Data: As the dataset is entirely simulated and does not reflect real-world scenarios or valid statistical patterns, models trained on this data are likely to develop misleading or inaccurate inferences.
2. Potential for Bias: Given the artificial creation of this data, there's a significant risk of introducing biases into models trained on it, which could lead to flawed conclusions or predictions when applied to real-world situations.
3. Ethical Considerations: The dataset was created with educational and research purposes in mind, specifically for theoretical exploration in the fields of operations research, supply chain management, and business management. Utilizing it for model training could lead to ethical concerns, particularly if such models are used for decision-making processes.
4. Integrity of Research: The primary intent of this dataset is to foster a learning environment and stimulate innovative research approaches. Using it for training models could undermine the integrity and objectives of research conducted with this resource.

By adhering to this guideline, users ensure that the dataset is utilized in a manner consistent with its intended purpose and ethical standards. We appreciate your cooperation in maintaining the dataset's role as a valuable educational and research tool.