In this work we show how to use a quantum adiabatic algorithm to solve multiobjective optimization problems. For the first time, we demonstrate a theorem proving that the quantum adiabatic algorithm can find Pareto-optimal solutions in finite-time, provided some restrictions to the problem are met. A numerical example illustrates an application of the theorem to a well-known problem in multiobjective optimization. This result opens the door to solve multiobjective optimization problems using current technology based on quantum annealing.
Adiabatic quantum annealing techniques are also used to address multiobjective optimization problems REF .
A Quantum Adiabatic Algorithm for Multiobjective Combinatorial Optimization
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Computer Science