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Optees is an open-source desktop toolkit for optimization: LP (SciPy/HiGHS), MILP (OR-Tools CP-SAT), and 0/1 knapsack. Clean Architecture, TDD, dataset adapters (LPnetlib, MIPLIB, Burkardt). Minimal APIs, extensible and testable.

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Optees

Optees is an open-source, cross-platform desktop application designed to make business optimization accessible to everyone, from technical experts to non-specialist personnel.

The goal is to provide a user-friendly tool that leverages powerful operational research algorithms to solve real-world business problems efficiently.

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Key Features

  • Interactive Chatbot: A guided assistant that helps users select the most suitable optimization algorithm for their specific needs.
  • Data Management: Easily import and manage data from common formats like CSV and Excel.
  • Robust Algorithms: A comprehensive suite of optimization algorithms for a wide range of problems, including resource management, scheduling, and logistics.
  • Clear Output: The application provides clear, actionable results with detailed explanations to help users understand the solution.

Installation

This project requires Python 3.12 or later.

  1. Clone the repository:
    git clone [https://github.com/your_username/optees.git](https://github.com/your_username/optees.git)
    cd optees
  2. Create and activate a virtual environment:
    conda env create -f environment.yml
    conda activate optees
  3. Install dependencies:
    pip install -r requirements.txt

About

Optees is an open-source desktop toolkit for optimization: LP (SciPy/HiGHS), MILP (OR-Tools CP-SAT), and 0/1 knapsack. Clean Architecture, TDD, dataset adapters (LPnetlib, MIPLIB, Burkardt). Minimal APIs, extensible and testable.

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