Faster QUBO Brute-Force Solving using Gray Code
This article describes an improved brute-force solving strategy for Quadratic Unconstrained Binary Optimization (QUBO) problems that is faster than naive approaches and easily parallelizable. It exploits the Gray code ordering of natural numbers to allow for a more efficient evaluation of the QUBO o...
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| Main Author | |
|---|---|
| Format | Journal Article |
| Language | English |
| Published |
30.10.2023
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| Subjects | |
| Online Access | Get full text |
| DOI | 10.48550/arxiv.2310.19373 |
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| Abstract | This article describes an improved brute-force solving strategy for Quadratic
Unconstrained Binary Optimization (QUBO) problems that is faster than naive
approaches and easily parallelizable. It exploits the Gray code ordering of
natural numbers to allow for a more efficient evaluation of the QUBO objective
function. The implementation in Python is discussed in detail, and an
additional C implementation is provided. |
|---|---|
| AbstractList | This article describes an improved brute-force solving strategy for Quadratic
Unconstrained Binary Optimization (QUBO) problems that is faster than naive
approaches and easily parallelizable. It exploits the Gray code ordering of
natural numbers to allow for a more efficient evaluation of the QUBO objective
function. The implementation in Python is discussed in detail, and an
additional C implementation is provided. |
| Author | Mücke, Sascha |
| Author_xml | – sequence: 1 givenname: Sascha surname: Mücke fullname: Mücke, Sascha |
| BackLink | https://doi.org/10.48550/arXiv.2310.19373$$DView paper in arXiv |
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| Snippet | This article describes an improved brute-force solving strategy for Quadratic
Unconstrained Binary Optimization (QUBO) problems that is faster than naive... |
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| SubjectTerms | Computer Science - Data Structures and Algorithms |
| Title | Faster QUBO Brute-Force Solving using Gray Code |
| URI | https://arxiv.org/abs/2310.19373 |
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