TY - JOUR
AU - Fedorov, Aleksey K.
AB - 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.
TI - Quantum and quantum-inspired optimization for an in-core fuel management problem
JF - Quantum Physics
DO - 10.48550/arxiv.2308.13348
DA - 2023-08-25
UR - https://www.deepdyve.com/lp/arxiv-cornell-university/quantum-and-quantum-inspired-optimization-for-an-in-core-fuel-NSZsw9W30c
VL - 2023
IS - 2308
DP - DeepDyve
ER -