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Improvement of Quantum Approximate Optimization Algorithm for Max-Cut Problems
DOI:10.3390/s22010244.png)
摘要
En 中文
The objective of this short letter is to study the optimal partitioning of value stream networks into two classes so that the number of connections between them is maximized. Such kind of problems are frequently found in the design of different systems such as communication network configuration, and industrial applications in which certain topological characteristics enhance value-stream network resilience. The main interest is to improve the Max-Cut algorithm proposed in the quantum approximate optimization approach (QAOA), looking to promote a more efficient implementation than those already published. A discussion regarding linked problems as well as further research questions are also reviewed.
Keyword:
Industry 4
0
quantum approximate optimization algorithm
value-stream networks
optimization
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期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison面向智能制造和工业4.0的数字孪生和大数据: 360度比较
IEEE ACCESS
IF3.6

