Quantum computing devices are believed to be powerful in solving hard computational tasks, in particular, combinatorial optimization problems. In the present work, we consider a particular type of the minimum bin packing problem, which can be used for solving the problem of filling spent nuclear fuel in deep-repository canisters that is relevant for atomic energy industry. We first redefine the aforementioned problem it in terms of quadratic unconstrained binary optimization. Such a representation is natively compatible with existing quantum annealing devices as well as quantum-inspired algorithms. We then present the results of the numerical comparison of quantum and quantum-inspired methods. Results of our study indicate on the possibility to solve industry-relevant problems of atomic energy industry using quantum and quantum-inspired optimization.
@article{arxiv.2301.11265,
title = {Quantum and quantum-inspired optimization for solving the minimum bin packing problem},
author = {A. A. Bozhedarov and A. S. Boev and S. R. Usmanov and G. V. Salahov and E. O. Kiktenko and A. K. Fedorov},
journal= {arXiv preprint arXiv:2301.11265},
year = {2024}
}