A Method for Large Scale Unconstrained Binary Quadratic Programming Problem Based on Graph Neural Network

In recent years, the advantages of Graph Neural Networks (GNNs) in solving complex combinatorial optimization problems have become more and more obvious. Under this background, this paper demonstrates a method based on GNNs to solve large-scale Unconstrained 0-1 Quadratic Programming (UBQP) problems...

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Veröffentlicht in:	International Conference on Intelligent Control and Information Processing (Online) S. 144 - 151
Hauptverfasser:	Huang, Jiajia, Gu, Shenshen
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 08.03.2024
Schlagworte:	Graph Attention Network Graph neural networks Optimization Quadratic programming Stability analysis Supervised learning Training Transfer learning Unconstrained 0-1 quadratic programming Unified graph model Unsupervised learning
ISSN:	2835-9577
Online-Zugang:	Volltext
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