quadratic unconstrained binary optimization of the fuel loading pattern in nuclear reactors

The loading pattern problem in nuclear reactors is a hard optimization problem with non convex and non linear objective function, this makes the optimization task for classical algorithms challenging . Over the last years , quantum annealing has shown promising results in solving large scale industrial optimization problems , this motivates the investigation of this method to the loading pattern problem . To be able to run an optimization problem on a quantum annealer , one should put it in a quadratic unconstrained binary optimization (QUBO) form . This is non trivial task due to the non linearity of the objective function . I have discussed how one may surmount this problem and and develop a QUBO for the LP problem and then run the QUBO on the D-Wave quantum simulator . The obtained results are satisfactory encouraging further exploration of the method to more complex settings in the loading pattern problem hoping to achieve better optimal configurations than those obtained via classical methods which can result in a big savings for nuclear power plants .