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For the traveling salesman problem (TSP), the existing supervised learning based algorithms suffer seriously from the lack of generalization ability.
An effective heuristic algorithm for the traveling-salesman problem
Shen Lin and Brian W Kernighan · 1973
Earlier work this paper cites.
The distance-weighted k-nearest-neighbor rule
Sahibsingh A Dudani · 1976
Earlier work this paper cites.
Neural computation of decisions in optimization problems
John J Hopfield and David W Tank · 1985
Earlier work this paper cites.
Tsplib—a traveling salesman problem library
Gerhard Reinelt · 1991
Earlier work this paper cites.
Variable neighborhood search
Nenad Mladenović and Pierre Hansen · 1997
Earlier work this paper cites.
Neural networks for combinatorial optimization: a review of more than a decade of research
Kate A Smith · 1999
Earlier work this paper cites.
An effective implementation of the lin–kernighan traveling salesman heuristic
Keld Helsgaun · 2000
Earlier work this paper cites.
Chained lin-kernighan for large traveling salesman problems
David Applegate, William Cook, and André Rohe · 2003
Earlier work this paper cites.
Concorde tsp solver. http://www.math.uwaterloo.ca/tsp/concorde, 2006
David Applegate, Ribert Bixby, Vasek Chvatal, and William Cook · 2006
Earlier work this paper cites.
Efficient selectivity and backup operators in monte-carlo tree search
Rémi Coulom · 2006
Earlier work this paper cites.
Certification of an optimal tsp tour through 85,900 cities
David L Applegate, Robert E Bixby, Vašek Chvátal, William Cook, Daniel G Espinoza, Marcos Goycoolea, and Keld Helsgaun · 2009
Earlier work this paper cites.
General k-opt submoves for the lin–kernighan tsp heuristic
Keld Helsgaun · 2009
Earlier work this paper cites.
Traveling salesman problem heuristics: Leading methods, implementations and latest advances
César Rego, Dorabela Gamboa, Fred Glover, and Colin Osterman · 2011
Earlier work this paper cites.
A survey of monte carlo tree search methods
Cameron B Browne, Edward Powley, Daniel Whitehouse, Simon M Lucas, Peter I Cowling, Philipp Rohlfshagen, Stephen Tavener, Diego Perez, Spyridon Samothrakis, and Simon Colton · 2012
Earlier work this paper cites.
Gurobi optimizer reference manual
Incorporate Gurobi Optimization · 2015
Earlier work this paper cites.
Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly · 2015
Cited alongside, same era.
Or-tools, google optimization tools
Google · 2016
Cited alongside, same era.
Application of monte-carlo tree search to traveling-salesman problem
Masato Shimomura and Yasuhiro Takashima · 2016
Cited alongside, same era.
Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
Cited alongside, same era.
Neural combinatorial optimization with reinforcement learning
Irwan Bello, Hieu Pham, Quoc V Le, Mohammad Norouzi, and Samy Bengio · 2017
Cited alongside, same era.
An extension of the lin-kernighan-helsgaun tsp solver for constrained traveling salesman and vehicle routing problems
Keld Helsgaun · 2017
Learning a sat solver from single-bit supervision
Daniel Selsam, Matthew Lamm, Benedikt Bünz, Percy Liang, Leonardo de Moura, and David L Dill · 2018
Later among the works it cites.
M-walk: Learning to walk over graphs using monte carlo tree search
Yelong Shen, Jianshu Chen, Po-Sen Huang, Yuqing Guo, and Jianfeng Gao · 2018
Later among the works it cites.
Learning to perform local rewriting for combinatorial optimization
Xinyun Chen and Yuandong Tian · 2019
Later among the works it cites.
Solving combinatorial problems with machine learning methods
Tiande Guo, Congying Han, Siqi Tang, and Man Ding · 2019
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An efficient graph convolutional network technique for the travelling salesman problem
Chaitanya K Joshi, Thomas Laurent, and Xavier Bresson · 2019
Later among the works it cites.
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Cited alongside, same era.
Learning combinatorial optimization algorithms over graphs
Elias Khalil, Hanjun Dai, Yuyu Zhang, Bistra Dilkina, and Le Song · 2017
Cited alongside, same era.
A note on learning algorithms for quadratic assignment with graph neural networks
Alex Nowak, Soledad Villar, Afonso S Bandeira, and Joan Bruna · 2017
Cited alongside, same era.
Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
Cited alongside, same era.
Machine learning for combinatorial optimization: a methodological tour d’horizon
Yoshua Bengio, Andrea Lodi, and Antoine Prouvost · 2018
Cited alongside, same era.
Learning heuristics for the tsp by policy gradient
Michel Deudon, Pierre Cournut, Alexandre Lacoste, Yossiri Adulyasak, and Louis-Martin Rousseau · 2018
Cited alongside, same era.
Learning permutations with sinkhorn policy gradient
Patrick Emami and Sanjay Ranka · 2018
Cited alongside, same era.
Learning the multiple traveling salesmen problem with permutation invariant pooling networks
Yoav Kaempfer and Lior Wolf · 2019
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Attention, learn to solve routing problems!
Wouter Kool, Herke van Hoof, and Max Welling · 2019
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Henrique Lemos, Marcelo Prates, Pedro Avelar, and Luis Lamb · 2019
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Learning to solve np-complete problems: A graph neural network for decision tsp
Marcelo Prates, Pedro HC Avelar, Henrique Lemos, Luis C Lamb, and Moshe Y Vardi · 2019
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Devavrat Shah, Qiaomin Xie, and Zhi Xu · 2019
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Popmusic for the travelling salesman problem
Éric D Taillard and Keld Helsgaun · 2019
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Learning combinatorial embedding networks for deep graph matching
Runzhong Wang, Junchi Yan, and Xiaokang Yang · 2019
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A learning-based iterative method for solving vehicle routing problems
Hao Lu, Xingwen Zhang, and Shuang Yang · 2020
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A graph neural network assisted monte carlo tree search approach to traveling salesman problem
Zhihao Xing and Shikui Tu · 2020
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