QAMin

QAMin is a software tool designed for the analysis and visualization of quadratic assignment problems (QAPs). The quadratic assignment problem is a classical combinatorial optimization challenge that involves assigning a set of facilities to a set of locations in a way that minimizes the total cost or distance, considering both the flow between facilities and the distance between locations. QAMin offers a platform for researchers and practitioners to solve, analyze, and compare solutions for these complex problems.

Developed with emphasis on efficiency and usability, QAMin incorporates various heuristic and exact algorithms, enabling users to handle large and complex instances of the QAP. It provides functionalities for generating initial solutions, improving these solutions iteratively, and visualizing assignment mappings to facilitate understanding and decision-making.

QAMin supports a range of input formats to accommodate different datasets and integrates with modeling environments such as MATLAB or Python to streamline workflows. Its modular architecture allows for customization and expansion, making it suitable for research applications as well as practical problem-solving in logistics, facility layout, and other fields requiring optimized assignment strategies.

The tool is part of ongoing efforts to enhance the computational methods for tackling quadratic assignment problems, which are known to be NP-hard, meaning that they are computationally intensive and challenging to solve optimally at scale. Through efficient algorithms and user-friendly features, QAMin aims to contribute to advancing solutions in operational research, industrial engineering, and logistics planning.

QAMin is freely available for academic and research use, with documentation and support provided by its development team. Its ongoing development focuses on integrating more advanced heuristic algorithms and improving scalability to serve a broader range of real-world applications.