Fetching the paper…
Reading the bibliography…
Learning heuristics for vehicle routing problems (VRPs) has gained much attention due to the less reliance on hand-crafted rules.
A method for solving traveling-salesman problems
Croes, G. A · 1958
Earlier work this paper cites.
Tsplib—a traveling salesman problem library
Reinelt, G · 1991
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Williams, R. J · 1992
Earlier work this paper cites.
Approche polyèdrale du problème de tournées de véhicules
Augerat, P · 1995
Earlier work this paper cites.
No free lunch theorems for optimization
Wolpert, D. H. and Macready, W. G · 1997
Earlier work this paper cites.
Using constraint programming and local search methods to solve vehicle routing problems
Shaw, P · 1998
Earlier work this paper cites.
An effective implementation of the lin–kernighan traveling salesman heuristic
Helsgaun, K · 2000
Earlier work this paper cites.
A perspective view and survey of meta-learning
Vilalta, R. and Drissi, Y · 2002
Earlier work this paper cites.
Curriculum learning
Bengio, Y., Louradour, J., Collobert, R., and Weston, J · 2009
Earlier work this paper cites.
Vehicle routing problems with alternative paths: An application to on-demand transportation
Garaix, T., Artigues, C., Feillet, D., and Josselin, D · 2010
Earlier work this paper cites.
Understanding tsp difficulty by learning from evolved instances
Smith-Miles, K., Hemert, J. v., and Lim, X. Y · 2010
Earlier work this paper cites.
Distilling the knowledge in a neural network
Hinton, G., Vinyals, O., and Dean, J · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2015
Earlier work this paper cites.
Pointer networks
Vinyals, O., Fortunato, M., and Jaitly, N · 2015
Earlier work this paper cites.
Neural combinatorial optimization with reinforcement learning
Bello, I., Pham, H., Le, Q. V., Norouzi, M., and Bengio, S · 2017
Earlier work this paper cites.
Bresson, X. and Laurent, T · 2017
Earlier work this paper cites.
Vehicle routing problems for city logistics
Cattaruzza, D., Absi, N., Feillet, D., and González-Feliu, J · 2017
Earlier work this paper cites.
Learning combinatorial optimization algorithms over graphs
Dai, H., Khalil, E. B., Zhang, Y., Dilkina, B., and Song, L · 2017
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Finn, C., Abbeel, P., and Levine, S · 2017
Earlier work this paper cites.
An extension of the lin-kernighan-helsgaun tsp solver for constrained traveling salesman and vehicle routing problems
Helsgaun, K · 2017
Earlier work this paper cites.
New benchmark instances for the capacitated vehicle routing problem
Uchoa, E., Pecin, D., Pessoa, A., Poggi, M., Vidal, T., and Subramanian, A · 2017
Earlier work this paper cites.
Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
Earlier work this paper cites.
Attention, learn to solve routing problems!
Kool, W., van Hoof, H., and Welling, M · 2018
Earlier work this paper cites.
Reinforcement learning for solving the vehicle routing problem
Nazari, M., Oroojlooy, A., Snyder, L., and Takác, M · 2018
Earlier work this paper cites.
On first-order meta-learning algorithms
Nichol, A., Achiam, J., and Schulman, J · 2018
Cited alongside, same era.
Learning large neighborhood search for vehicle routing in airport ground handling
Zhou, J., Wu, Y., Cao, Z., Song, W., Zhang, J., and Chen, Z · 2018
Cited alongside, same era.
Evolving diverse tsp instances by means of novel and creative mutation operators
Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., and Trautmann, H · 2019
Cited alongside, same era.
Learning to perform local rewriting for combinatorial optimization
Chen, X. and Tian, Y · 2019
Cited alongside, same era.
An efficient graph convolutional network technique for the travelling salesman problem
Joshi, C. K., Laurent, T., and Bresson, X · 2019
Cited alongside, same era.
Learning to delegate for large-scale vehicle routing
Li, S., Yan, Z., and Wu, C · 2021
Later among the works it cites.
Learning to iteratively solve routing problems with dual-aspect collaborative transformer
Ma, Y., Li, J., Cao, Z., Song, W., Zhang, L., Chen, Z., and Tang, J · 2021
Later among the works it cites.
A bi-level framework for learning to solve combinatorial optimization on graphs
Wang, R., Hua, Z., Liu, G., Zhang, J., Yan, J., Qi, F., Yang, S., Zhou, J., and Yang, X · 2021
Later among the works it cites.
Learning improvement heuristics for solving routing problems
Wu, Y., Song, W., Cao, Z., Zhang, J., and Lim, A · 2021
Later among the works it cites.
Attention, filling in the gaps for generalization in routing problems
Bdeir, A., Falkner, J. K., and Schmidt-Thieme, L · 2022
Later among the works it cites.
Learning generalizable models for vehicle routing problems via knowledge distillation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ma, Q., Ge, S., He, D., Thaker, D., and Drori, I · 2019
Cited alongside, same era.
Learning a sat solver from single-bit supervision
Selsam, D., Lamm, M., Bünz, B., Liang, P., de Moura, L., and Dill, D. L · 2019
Cited alongside, same era.
Learning what to defer for maximum independent sets
Ahn, S., Seo, Y., and Shin, J · 2020
Cited alongside, same era.
Learning 2-opt heuristics for the traveling salesman problem via deep reinforcement learning
d O Costa, P. R., Rhuggenaath, J., Zhang, Y., and Akcay, A · 2020
Cited alongside, same era.
Neural large neighborhood search for the capacitated vehicle routing problem
Hottung, A. and Tierney, K · 2020
Cited alongside, same era.
Pomo: Policy optimization with multiple optima for reinforcement learning
Kwon, Y.-D., Choo, J., Kim, B., Yoon, I., Gwon, Y., and Min, S · 2020
Cited alongside, same era.
Evaluating curriculum learning strategies in neural combinatorial optimization
Lisicki, M., Afkanpour, A., and Taylor, G. W · 2020
Cited alongside, same era.
Bi, J., Ma, Y., Wang, J., Cao, Z., Chen, J., Sun, Y., and Chee, Y. M · 2022
Later among the works it cites.
Bootstrapped meta-learning
Flennerhag, S., Schroecker, Y., Zahavy, T., van Hasselt, H., Silver, D., and Singh, S · 2022
Later among the works it cites.
Generalization of neural combinatorial solvers through the lens of adversarial robustness
Geisler, S., Sommer, J., Schuchardt, J., Bojchevski, A., and Günnemann, S · 2022
Later among the works it cites.
Efficient active search for combinatorial optimization problems
Hottung, A., Kwon, Y.-D., and Tierney, K · 2022
Later among the works it cites.
Graph neural network guided local search for the traveling salesperson problem
Hudson, B., Li, Q., Malencia, M., and Prorok, A · 2022
Later among the works it cites.
Learning to solve routing problems via distributionally robust optimization
Jiang, Y., Wu, Y., Cao, Z., and Zhang, J · 2022
Later among the works it cites.
Scale-conditioned adaptation for large scale combinatorial optimization
Kim, M., SON, J., Kim, H., and Park, J · 2022
Later among the works it cites.
Vehicle routing problem and related algorithms for logistics distribution: A literature review and classification
Konstantakopoulos, G. D., Gayialis, S. P., and Kechagias, E. P · 2022
Later among the works it cites.
How good is neural combinatorial optimization?
Liu, S., Zhang, Y., Tang, K., and Yao, X · 2022
Later among the works it cites.
On the generalization of neural combinatorial optimization heuristics
Manchanda, S., Michel, S., Drakulic, D., and Andreoli, J.-M · 2022
Later among the works it cites.
DIMES: A differentiable meta solver for combinatorial optimization problems
Qiu, R., Sun, Z., and Yang, Y · 2022
Later among the works it cites.
10,000 optimal cvrp solutions for testing machine learning based heuristics
Queiroga, E., Sadykov, R., Uchoa, E., and Vidal, T · 2022
Later among the works it cites.
Hybrid genetic search for the cvrp: Open-source implementation and swap* neighborhood
Vidal, T · 2022
Later among the works it cites.
A game-theoretic approach for improving generalization ability of tsp solvers
Wang, C., Yang, Y., Slumbers, O., Han, C., Guo, T., Zhang, H., and Wang, J · 2022
Later among the works it cites.
Learning to solve travelling salesman problem with hardness-adaptive curriculum
Zhang, Z., Zhang, Z., Wang, X., and Zhu, W · 2022
Later among the works it cites.
Bq-nco: Bisimulation quotienting for generalizable neural combinatorial optimization
Drakulic, D., Michel, S., Mai, F., Sors, A., and Andreoli, J.-M · 2023
Closest in time.
Generalize learned heuristics to solve large-scale vehicle routing problems in real-time
Hou, Q., Yang, J., Su, Y., Wang, X., and Deng, Y · 2023
Closest in time.
Difusco: Graph-based diffusion solvers for combinatorial optimization
Sun, Z. and Yang, Y · 2023
Closest in time.
Neural airport ground handling
Wu, Y., Zhou, J., Xia, Y., Zhang, X., Cao, Z., and Zhang, J · 2023
Closest in time.