Improvement of Quantum Approximate Optimization Algorithm for Max–Cut Problems

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, an...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-12, Vol.22 (1), p.244, Article 244
Main Authors: Villalba-Diez, Javier, González-Marcos, Ana, Ordieres-Meré, Joaquín B
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Communication
Connectivity
Industrial applications
Industry 4.0
Internet of Things
Manufacturing
optimization
Optimization algorithms
Production planning
quantum approximate optimization algorithm
Value chain
value–stream networks
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22010244