Performance of the Extended Ising Machine for the Quadratic Knapsack Problem

The extended Ising machine (EIM) enhances conventional Ising models, which handle only binary quadratic forms by allowing constraints through real-valued dependent variables. We address the quadratic knapsack problem (QKP), hard to solve using Ising machines when formulated as a quadratic unconstrained binary optimization (QUBO). We demonstrated the EIM's superiority by comparing it with the conventional Ising model-based approach, a commercial exact solver, and a state-of-the-art heuristic solver for QKP.

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Publication Details

Journal
Journal of the Physical Society of Japan
Published
2025-08-08
DOI
https://doi.org/10.7566/jpsj.94.095002
Primary Topic
Machine Learning and Algorithms
Type
article
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article

Performance of the Extended Ising Machine for the Quadratic Knapsack Problem

Kazue Kudo, Hirotaka Tamura, Haruka Akishima
Journal of the Physical Society of Japan
Machine Learning and Algorithms
article

Performance of the Extended Ising Machine for the Quadratic Knapsack Problem

Kazue Kudo, Hirotaka Tamura, Haruka Akishima
article en

Abstract

The extended Ising machine (EIM) enhances conventional Ising models, which handle only binary quadratic forms by allowing constraints through real-valued dependent variables. We address the quadratic knapsack problem (QKP), hard to solve using Ising machines when formulated as a quadratic unconstrained binary optimization (QUBO). We demonstrated the EIM's superiority by comparing it with the conventional Ising model-based approach, a commercial exact solver, and a state-of-the-art heuristic solver for QKP.

Journal of the Physical Society of JapanVol. 94(9)
Tohoku University (JP), Ochanomizu University (JP), Socionext (Japan) (JP)
Openalex Percentile: Top 89%
Machine Learning and Algorithms
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