Performance of the Extended Ising Machine for the Quadratic Knapsack Problem
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866912532280639488 |
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| author | Akishima, Haruka Tamura, Hirotaka Kudo, Kazue |
| author_facet | Akishima, Haruka Tamura, Hirotaka Kudo, Kazue |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2508_06909 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Performance of the Extended Ising Machine for the Quadratic Knapsack Problem Akishima, Haruka Tamura, Hirotaka Kudo, Kazue Statistical Mechanics Data Structures and Algorithms 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. |
| title | Performance of the Extended Ising Machine for the Quadratic Knapsack Problem |
| topic | Statistical Mechanics Data Structures and Algorithms |
| url | https://arxiv.org/abs/2508.06909 |