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Routing problems are a class of combinatorial problems with many practical applications.
On the theory of dynamic programming
Richard Bellman · 1952
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Edsger W Dijkstra · 1959
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Dynamic programming treatment of the travelling salesman problem
Richard Bellman · 1962
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The vehicle routing problem: An overview of exact and approximate algorithms
Gilbert Laporte · 1992
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An optimal algorithm for the traveling salesman problem with time windows
Yvan Dumas, Jacques Desrosiers, Eric Gelinas, and Marius M Solomon · 1995
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Chryssi Malandraki and Robert B Dial · 1996
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Aristide Mingozzi, Lucio Bianco, and Salvatore Ricciardelli · 1997
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Record breaking optimization results using the ruin and recreate principle
Gerhard Schrimpf, Johannes Schneider, Hermann Stamm-Wilbrandt, and Gunter Dueck · 2000
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Tour merging via branch-decomposition
William Cook and Paul Seymour · 2003
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Learning as search optimization: Approximate large margin methods for structured prediction
Hal Daumé III and Daniel Marcu · 2005
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Concorde TSP solver, 2006
David Applegate, Robert Bixby, Vasek Chvatal, and William Cook · 2006
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An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows
Stefan Ropke and David Pisinger · 2006
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An approximate dynamic programming approach for the vehicle routing problem with stochastic demands
Clara Novoa and Robert Storer · 2009
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A general vns heuristic for the traveling salesman problem with time windows
Rodrigo Ferreira Da Silva and Sebastián Urrutia · 2010
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A dynamic programming heuristic for vehicle routing with time-dependent travel times and required breaks
AL Kok, Elias W Hans, Johannes MJ Schutten, and Willem HM Zijm · 2010
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Restricted dynamic programming: a flexible framework for solving realistic vrps
Joaquim Gromicho, Jelke J van Hoorn, Adrianus Leendert Kok, and Johannes MJ Schutten · 2012
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Solving the job-shop scheduling problem optimally by dynamic programming
Joaquim AS Gromicho, Jelke J Van Hoorn, Francisco Saldanha-da Gama, and Gerrit T Timmer · 2012
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A hybrid genetic algorithm for multidepot and periodic vehicle routing problems
Thibaut Vidal, Teodor Gabriel Crainic, Michel Gendreau, Nadia Lahrichi, and Walter Rei · 2012
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Vehicle routing: problems, methods, and applications
Paolo Toth and Daniele Vigo · 2014
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly · 2015
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Neural combinatorial optimization with reinforcement learning
Irwan Bello, Hieu Pham, Quoc V Le, Mohammad Norouzi, and Samy Bengio · 2016
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Dynamic Programming for Routing and Scheduling
Jelke J. van Hoorn · 2016
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Sequence-to-sequence learning as beam-search optimization
Sam Wiseman and Alexander M Rush · 2016
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An extension of the Lin-Kernighan-Helsgaun TSP solver for constrained traveling salesman and vehicle routing problems: Technical report
Keld Helsgaun · 2017
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A note on learning algorithms for quadratic assignment with graph neural networks
Alex Nowak, Soledad Villar, Afonso S Bandeira, and Joan Bruna · 2017
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Learning improvement heuristics for solving routing problems
Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, and Andrew Lim · 2019
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A fast and scalable heuristic for the solution of large-scale capacitated vehicle routing problems
Luca Accorsi and Daniele Vigo · 2020
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Combining reinforcement learning and constraint programming for combinatorial optimization
Quentin Cappart, Thierry Moisan, Louis-Martin Rousseau, Isabeau Prémont-Schwarz, and Andre Cire · 2020
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Learning 2-opt heuristics for the traveling salesman problem via deep reinforcement learning
Paulo Roberto de O da Costa, Jason Rhuggenaath, Yingqian Zhang, and Alp Akcay · 2020
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Reinforcement learning with combinatorial actions: An application to vehicle routing
Arthur Delarue, Ross Anderson, and Christian Tjandraatmadja · 2020
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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New benchmark instances for the capacitated vehicle routing problem
Eduardo Uchoa, Diego Pecin, Artur Pessoa, Marcus Poggi, Thibaut Vidal, and Anand Subramanian · 2017
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Learning heuristics for the TSP by policy gradient
Michel Deudon, Pierre Cournut, Alexandre Lacoste, Yossiri Adulyasak, and Louis-Martin Rousseau · 2018
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Gurobi Optimization, LLC · 2018
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Combinatorial optimization with graph convolutional networks and guided tree search
Zhuwen Li, Qifeng Chen, and Vladlen Koltun · 2018
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Reinforcement learning for solving the vehicle routing problem
MohammadReza Nazari, Afshin Oroojlooy, Lawrence Snyder, and Martin Takac · 2018
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A general reinforcement learning algorithm that masters chess, shogi, and go through self-play
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, et al · 2018
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Learning to solve vehicle routing problems with time windows through joint attention
Jonas K Falkner and Lars Schmidt-Thieme · 2020
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Generalize a small pre-trained model to arbitrarily large tsp instances
Zhang-Hua Fu, Kai-Bin Qiu, and Hongyuan Zha · 2020
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Learn to design the heuristics for vehicle routing problem
Lei Gao, Mingxiang Chen, Qichang Chen, Ganzhong Luo, Nuoyi Zhu, and Zhixin Liu · 2020
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Pomo: Policy optimization with multiple optima for reinforcement learning
Yeong-Dae Kwon, Jinho Choo, Byoungjip Kim, Iljoo Yoon, Youngjune Gwon, and Seungjai Min · 2020
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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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Reinforcement learning for combinatorial optimization: A survey
Nina Mazyavkina, Sergey Sviridov, Sergei Ivanov, and Evgeny Burnaev · 2020
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Solving mixed integer programs using neural networks
Vinod Nair, Sergey Bartunov, Felix Gimeno, Ingrid von Glehn, Pawel Lichocki, Ivan Lobov, Brendan O’Donoghue, Nicolas Sonnerat, Christian Tjandraatmadja, Pengming Wang, et al · 2020
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Generalization of machine learning for problem reduction: a case study on travelling salesman problems
Yuan Sun, Andreas Ernst, Xiaodong Li, and Jake Weiner · 2020
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Learning combinatorial optimization on graphs: A survey with applications to networking
Natalia Vesselinova, Rebecca Steinert, Daniel F Perez-Ramirez, and Magnus Boman · 2020
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Hybrid genetic search for the cvrp: Open-source implementation and swap* neighborhood
Thibaut Vidal · 2020
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Step-wise deep learning models for solving routing problems
Liang Xin, Wen Song, Zhiguang Cao, and Jie Zhang · 2020
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Deep neural network approximated dynamic programming for combinatorial optimization
Shenghe Xu, Shivendra S Panwar, Murali Kodialam, and TV Lakshman · 2020
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Learning a latent search space for routing problems using variational autoencoders
André Hottung, Bhanu Bhandari, and Kevin Tierney · 2021
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Learning collaborative policies to solve np-hard routing problems
Minsu Kim, Jinkyoo Park, and Joungho Kim · 2021
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Learning to delegate for large-scale vehicle routing
Sirui Li, Zhongxia Yan, and Cathy Wu · 2021
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Learning to iteratively solve routing problems with dual-aspect collaborative transformer
Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, and Jing Tang · 2021
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NeuroLKH: Combining deep learning model with lin-kernighan-helsgaun heuristic for solving the traveling salesman problem
Liang Xin, Wen Song, Zhiguang Cao, and Jie Zhang · 2021
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