Quantum and quantum-inspired optimization for an in-core fuel management problem
Abstract
Operation management of nuclear power plants consists of several computationally hard problems. Searching for an in-core fuel loading pattern is among them. The main challenge of this combinatorial optimization problem is the exponential growth of the search space with a number of loading elements. Here we study a reloading problem in a Quadratic Unconstrained Binary Optimization (QUBO) form. Such a form allows us to apply various techniques, including quantum annealing, classical simulated annealing, and quantum-inspired algorithms in order to find fuel reloading patterns for several realistic configurations of nuclear reactors. We present the results of benchmarking the in-core fuel management problem in the QUBO form using the aforementioned computational techniques. This work demonstrates potential applications of quantum computers and quantum-inspired algorithms in the energy industry.
Cite
@article{arxiv.2308.13348,
title = {Quantum and quantum-inspired optimization for an in-core fuel management problem},
author = {Sergey R. Usmanov and Gleb V. Salakhov and Anton A. Bozhedarov and Evgeniy O. Kiktenko and Aleksey K. Fedorov},
journal= {arXiv preprint arXiv:2308.13348},
year = {2024}
}
Comments
8+3 pages, 4+2 figures