Solving assignment problems via Quantum Computing: a case-study in train seating arrangement.

In recent years, researchers have oriented their studies towards new technologies based on quantum physics that should resolve complex problems currently considered to be intractable. This new research area is called Quantum Computing. What makes Quantum Computing so attractive is the particular way with which quantum technology operates and the great potential it can offer to solve real-world problems. This work focuses on solving assignment-like combinatorial optimization problems by exploiting this novel computational approach. A case-study, denoted as the Seating Arrangement Optimization problem, is considered. It is modeled through the Quadratic Unconstrained Binary Optimization paradigm and solved through two tools made available by the D-Wave Systems company, QBSolv, and a quantum-classical hybrid system. The obtained experimental results are compared in terms of solution quality and computational efficiency.