APDCM 2022 Keynote Talk: Solving QUBOs on Digital and Quantum Computers

Combinatorial Optimization searches for an optimum object in a finite but usually vast collection of objects. This can be used for many practical purposes, like efficient allocation of limited resources, network planning, and hundreds of other applications in almost all fields, e.g., finance, production, scheduling, and inventory control. However, many combinatorial optimization problems are known to be NP-hard, which is often translated simplistically as “intractable.” It is regularly claimed that quantum computers will bring breakthrough progress in solving such challenging combinatorial optimization problems relevant in practice. In particular, Quadratic Unconstraint Binary Optimization (QUBO) problems are said to be the model of choice for use in (adiabatic) quantum systems. We explain some of the meaning and implications, review the state of affairs, and give some computational results to underpin our conclusions.