QUBO formulations and characterization of penalty parameters for the multi-knapsack problem

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01A - Beitrag in wissenschaftlicher Zeitschrift
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Herausgeber:in (Körperschaft)
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Übergeordnetes Werk
IEEE Access
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Reihennummer
Jahrgang / Band
13
Ausgabe / Nummer
Seiten / Dauer
47086-47098
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IEEE
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Zusammenfassung
The Multi-Knapsack Problem (MKP) is a fundamental challenge in operations research and combinatorial optimization. Quantum computing introduces new possibilities for solving MKP using Quadratic Unconstrained Binary Optimization (QUBO) models. However, a key challenge in QUBO formulations is the selection of penalty parameters, which directly influence solution feasibility and algorithm performance. In this work, we develop QUBO formulations for two MKP variants—the Multidimensional Knapsack Problem (MDKP) and the Multiple Knapsack Problem (MUKP)—and provide an algebraic characterization of their penalty parameters. We systematically evaluate their impact through quantum simulation experiments and compare the performance of the two leading quantum optimization approaches: Quantum Approximate Optimization Algorithm (QAOA) and quantum annealing, alongside a state-of-the-art classical solver. Our results indicate that while classical solvers remain superior, careful tuning of penalty parameters significantly affects quantum optimization outcomes. QAOA is highly sensitive to parameter choices, whereas quantum annealing produces more stable results on small to mid-sized instances. Finally, we outline directions for future research in solvingMKP, including adaptive penalty parameter tuning, hybrid quantum-classical approaches, and practical optimization strategies for QAOA, as well as real-hardware evaluations.
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ISBN
ISSN
2169-3536
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Gold
Lizenz
'https://creativecommons.org/licenses/by/4.0/'
Zitation
Güney, E., Ehrenthal, J., & Hanne, T. (2025). QUBO formulations and characterization of penalty parameters for the multi-knapsack problem. IEEE Access, 13, 47086–47098. https://doi.org/10.1109/ACCESS.2025.3550788