ASP: Learn a Universal Neural Solver

Applying machine learning to combinatorial optimization problems has the potential to improve both efficiency and accuracy. However, existing learning-based solvers often struggle with generalization when faced with changes in problem distributions and scales. In this paper, we propose a new approac...

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Vydané v:	IEEE transactions on pattern analysis and machine intelligence Ročník 46; číslo 6; s. 4102 - 4114
Hlavní autori:	Wang, Chenguang, Yu, Zhouliang, McAleer, Stephen, Yu, Tianshu, Yang, Yaodong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation models Combinatorial analysis Combinatorial optimization problems curriculum learning generalization ability and scalability Machine learning Optimization policy space response oracles Scalability Solvers Training Traveling salesman problem Traveling salesman problems Vehicle routing
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
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