Operations Research 2025
Abstract Submission

80. Comparison of Quantum Approximate Optimization Algorithm across a variety of problems

Invited abstract in session TA-7: Quantum Computing & OR, stream Simulation and Quantum Computing.

Thursday, 8:45-10:15
Room: U2-205

Authors (first author is the speaker)

1. Sascha-André Schuster
Institute for Theoretical Computer Science, Mathematics and Operations Research, University of the Bundeswehr Munich
2. Rudy Milani
Universität der Bundeswehr München
3. Maximilian Moll
Universität der Bundeswehr München
4. Stefan Wolfgang Pickl
Department of Computer Science, UBw München COMTESSA

Abstract

Quantum computing offers interesting avenues to tackle computationally intensive problems in operations research. In this work, we perform a systematic comparison of variants of the Quantum Approximate Optimization Algorithm (QAOA) applied to several combinatorial optimization problems. The QAOA variants considered vary in the design of their employed Hamiltonians and parameterization techniques. Each variant is assessed in terms of its task performance and efficiency as well as required resources (number of qubits). A secondary goal of this study is the delivery of benchmark results beyond the commonly studied Max-Cut problem which dominates the literature. The results achieved provide grounds for further evaluations including real quantum hardware.

Keywords

Status: accepted

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