What is Qaekwy ?

Qaekwy is a powerful and flexible constraint-based modelling and optimization framework designed to tackle complex problem-solving scenarios. Whether you’re navigating resource allocation, scheduling, planning, or other intricate challenges, Qaekwy provides a comprehensive solution to formulate, solve, and optimize constraint-based problems.

Key Features

  • Modular Modelling: Qaekwy enables you to construct problem models using a modular and intuitive approach. Define variables, constraints, and objectives to encapsulate the intricacies of your problem domain.

  • Constraint-based Approach: By formulating problems as constraints, you express the relationships and limitations within your problem. This approach empowers you to model a wide range of real-world scenarios and leverage the solver’s capabilities.

  • Optimization Objectives: Qaekwy allows you to define optimization objectives that guide the solver towards finding solutions aligned with your goals. Whether minimizing or maximizing specific variables, the framework tailors solutions to your objectives.

  • Engine Flexibility: The DirectEngine offers seamless interaction with the Qaekwy cloud solver. The Engine (coming soon) empowers you to run the solver on your infrastructure. The ClusterEngine (coming soon) efficiently manages problems solving and Qaekwy cluster management at scale.

  • Solutions: Retrieve solutions from the solver to gain a comprehensive understanding of your problem’s resolution. The solution representation simplifies result interpretation in Python.

How Qaekwy Works

  • Model Formulation: Create a model by defining variables, constraints, and objectives using the Qaekwy classes.

  • Engine Interaction: Choose an appropriate Qaekwy engine for your needs, such as the DirectEngine for cloud interaction. Submit your model to the engine for solving.

  • Solving Process: Qaekwy’s solver employs advanced techniques to navigate the constraint space and search for solutions that meet the defined objectives.

  • Solution Retrieval: Retrieve the solutions generated by the solver, which are represented as variable assignments, or in dictionary mode, that satisfy the constraints and optimization goals.

Getting Started

To begin utilizing Qaekwy’s capabilities, consider exploring our documentation, examples, and tutorials. Whether you’re new to constraint-based modelling or an experienced practitioner, it empowers you to model and solve complex problems efficiently and effectively.

Incorporate this Python library into your software to address a wide range of challenges, optimize resource utilization, streamline processes, and make informed decisions based on simple modelling techniques !