OptiQAP

OptiQAP (PKOS id qap-solver) is a research-oriented solver toolkit for the Quadratic Assignment Problem (QAP), an NP-hard combinatorial optimization problem that appears in layout, assignment, and mapping tasks. The canonical repository is alawein/optiqap, with qap-solver as an alias. The project carries a P2 priority and is tagged with quantum-computing, optimization, HPC, and computational-physics.

In a quantum-computing context, QAP-style formulations are commonly used for qubit-to-hardware mapping and constraint-aware placement, making this project a natural bridge between combinatorial optimization research and near-term quantum systems. This aligns with the broader research profile of Meshal Alawein, a computational physicist whose work spans quantum computing, high-performance physics simulations, and AI governance. OptiQAP is directly linked to the meshal-alawein profile record, reflecting its significance within the overall research portfolio.

The project is implemented in Python, chosen for rapid research iteration. A modular implementation snapshot containing a multi-solver benchmark framework was imported to imports/qap-modular-repo/ on 2026-03-13 and is retained for staged integration into the main codebase. This modular architecture supports benchmarking multiple solver strategies against standard QAP problem instances.

The project is currently in the research phase, distinguishing it from the active-development phase of most other alawein projects. It sits at the intersection of Meshal's quantum computing and HPC domains.