Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

doi:10.1109/JAS.2023.124113

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	Learning to Branch in Combinatorial Optimization With Graph Pointer Networks
	Rui Wang; Zhiming Zhou; Kaiwen Li; Tao Zhang; Ling Wang; Xin Xu; Xiangke Liao
刊名	IEEE/CAA Journal of Automatica Sinica
	2024
卷号	11 期号:1 页码:157-169
关键词	Branch-and-bound (B&B) combinatorial optimization deep learning graph neural network imitation learning
ISSN号	2329-9266
DOI	10.1109/JAS.2023.124113
英文摘要	Traditional expert-designed branching rules in branch-and-bound (B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems. Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54500]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Rui Wang,Zhiming Zhou,Kaiwen Li,et al. Learning to Branch in Combinatorial Optimization With Graph Pointer Networks[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(1):157-169.
APA	Rui Wang.,Zhiming Zhou.,Kaiwen Li.,Tao Zhang.,Ling Wang.,...&Xiangke Liao.(2024).Learning to Branch in Combinatorial Optimization With Graph Pointer Networks.IEEE/CAA Journal of Automatica Sinica,11(1),157-169.
MLA	Rui Wang,et al."Learning to Branch in Combinatorial Optimization With Graph Pointer Networks".IEEE/CAA Journal of Automatica Sinica 11.1(2024):157-169.