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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Vydané v:	International Conference on Intelligent Control and Information Processing (Online) s. 144 - 151
Hlavní autori:	Huang, Jiajia, Gu, Shenshen
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 08.03.2024
Predmet:	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
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