QOPTec: a modular platform for benchmarking quantum algorithms through combinatorial optimization problems

Combinatorial optimization is a critical field in many applications that remains challenging due to its general computational complexity. Quantum computing is believed to be a promising alternative to classical methods to solve these types of problems. We introduce QOPTec, a Python library for benchmarking optimization problems using quantum or hybrid solvers. QOPTec offers a simple, extensible framework for reproducible evaluation of solver performance. By enabling integration of new problems and algorithms, the tool aims to lower the entry barrier to quantum optimization and supports systematic studies of different solver approaches, helping assess their practical potential as quantum technologies evolve.