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Learning how to automatically solve optimization problems has the potential to provide the next big leap in optimization technology.
The truck dispatching problem
G. B. Dantzig and J. H. Ramser · 1959
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Optimization by simulated annealing
S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi · 1983
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Neural computation of decisions in optimization problems
J. J. Hopfield and D. W. Tank · 1985
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. J. Williams · 1992
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Using constraint programming and local search methods to solve vehicle routing problems
P. Shaw · 1998
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A lower bound for the split delivery vehicle routing problem
J.-M. Belenguer, M. Martinez, and E. Mota · 2000
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An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows
S. Ropke and D. Pisinger · 2006
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A hybrid genetic algorithm for multidepot and periodic vehicle routing problems
T. Vidal, T. G. Crainic, M. Gendreau, N. Lahrichi, and W. Rei · 2012
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Sequence to sequence learning with neural networks
I. Sutskever, O. Vinyals, and Q. V. Le · 2014
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A unified solution framework for multi-attribute vehicle routing problems
T. Vidal, T. G. Crainic, M. Gendreau, and C. Prins · 2014
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An iterated local search heuristic for the split delivery vehicle routing problem
M. M. Silva, A. Subramanian, and L. S. Ochi · 2015
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Pointer networks
O. Vinyals, M. Fortunato, and N. Jaitly · 2015
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Neural combinatorial optimization with reinforcement learning
I. Bello, H. Pham, Q. V. Le, M. Norouzi, and S. Bengio · 2016
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A fresh ruin & recreate implementation for the capacitated vehicle routing problem
J. Christiaens and G. Vanden Berghe · 2016
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Algorithm selection for combinatorial search problems: A survey
L. Kotthoff · 2016
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P. Veličković, G. Cucurull, A. Casanova, A. Romero, P. Lio, and Y. Bengio · 2017
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Hyper-reactive tabu search for maxsat
C. Ansótegui, B. Heymann, J. Pon, M. Sellmann, and K. Tierney · 2018
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Machine learning for combinatorial optimization: a methodological tour d’horizon
Y. Bengio, A. Lodi, and A. Prouvost · 2018
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Learning heuristics for the TSP by policy gradient
M. Deudon, P. Cournut, A. Lacoste, Y. Adulyasak, and L.-M. Rousseau · 2018
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Learning the multiple traveling salesmen problem with permutation invariant pooling networks
Y. Kaempfer and L. Wolf · 2018
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X. Bresson and T. Laurent · 2017
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An extension of the Lin-Kernighan-Helsgaun TSP solver for constrained traveling salesman and vehicle routing problems
K. Helsgaun · 2017
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Learning combinatorial optimization algorithms over graphs
E. Khalil, H. Dai, Y. Zhang, B. Dilkina, and L. Song · 2017
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A note on learning algorithms for quadratic assignment with graph neural networks
A. Nowak, S. Villar, A. S. Bandeira, and J. Bruna · 2017
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Learning heuristic selection using a time delay neural network for open vehicle routing
R. Tyasnurita, E. Özcan, and R. John · 2017
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New benchmark instances for the capacitated vehicle routing problem
E. Uchoa, D. Pecin, A. Pessoa, M. Poggi, T. Vidal, and A. Subramanian · 2017
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Reinforcement learning for solving the vehicle routing problem
M. Nazari, A. Oroojlooy, L. Snyder, and M. Takác · 2018
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An efficient graph convolutional network technique for the travelling salesman problem
C. K. Joshi, T. Laurent, and X. Bresson · 2019
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Attention, learn to solve routing problems!
W. Kool, H. van Hoof, and M. Welling · 2019
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Neural network based large neighborhood search algorithm for ride hailing services
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Deep learning assisted heuristic tree search for the container pre-marshalling problem
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