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The end-to-end neural combinatorial optimization (NCO) method shows promising performance in solving complex combinatorial optimization problems without the need for expert design.
TSPLIB–a traveling salesman problem library
Reinelt, G · 1991
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Concorde tsp solver, 2006
Applegate, D., Bixby, R., Chvatal, V., and Cook, W · 2006
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Vehicle routing problems with alternative paths: An application to on-demand transportation
Garaix, T., Artigues, C., Feillet, D., and Josselin, D · 2010
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Heuristic search: theory and applications
Edelkamp, S. and Schrödl, S · 2011
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Complexity and approximation: Combinatorial optimization problems and their approximability properties
Ausiello, G., Crescenzi, P., Gambosi, G., Kann, V., Marchetti-Spaccamela, A., and Protasi, M · 2012
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Principles of genetic circuit design
Brophy, J. A. and Voigt, C. A · 2014
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
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Pointer networks
Vinyals, O., Fortunato, M., and Jaitly, N · 2015
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Neural combinatorial optimization with reinforcement learning
Bello, I., Pham, H., Le, Q. V., Norouzi, M., and Bengio, S · 2016
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An extension of the lin-kernighan-helsgaun tsp solver for constrained traveling salesman and vehicle routing problems
Helsgaun, K · 2017
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New benchmark instances for the capacitated vehicle routing problem
Uchoa, E., Pecin, D., Pessoa, A., Poggi, M., Vidal, T., and Subramanian, A · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
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Learning heuristics for the tsp by policy gradient
Deudon, M., Cournut, P., Lacoste, A., Adulyasak, Y., and Rousseau, L.-M · 2018
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Attention, learn to solve routing problems!
Kool, W., Van Hoof, H., and Welling, M · 2018
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Reinforcement learning for solving the vehicle routing problem
Nazari, M., Oroojlooy, A., Snyder, L., and Takác, M · 2018
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An efficient graph convolutional network technique for the travelling salesman problem
Joshi, C. K., Laurent, T., and Bresson, X · 2019
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A learning-based iterative method for solving vehicle routing problems
Lu, H., Zhang, X., and Yang, S · 2019
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Neural large neighborhood search for the capacitated vehicle routing problem
Hottung, A. and Tierney, K · 2020
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Pomo: Policy optimization with multiple optima for reinforcement learning
Kwon, Y.-D., Choo, J., Kim, B., Yoon, I., Gwon, Y., and Min, S · 2020
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Step-wise deep learning models for solving routing problems
Multi-decoder attention model with embedding glimpse for solving vehicle routing problems
Xin, L., Song, W., Cao, Z., and Zhang, J · 2021
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Simulation-guided beam search for neural combinatorial optimization
Choo, J., Kwon, Y.-D., Kim, J., Jae, J., Hottung, A., Tierney, K., and Gwon, Y · 2022
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Sym-nco: Leveraging symmetricity for neural combinatorial optimization
Kim, M., Park, J., and Park, J · 2022
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Deep policy dynamic programming for vehicle routing problems
Kool, W., van Hoof, H., Gromicho, J., and Welling, M · 2022
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DIMES: A differentiable meta solver for combinatorial optimization problems
Qiu, R., Sun, Z., and Yang, Y · 2022
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Xin, L., Song, W., Cao, Z., and Zhang, J · 2020
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Rbg: Hierarchically solving large-scale routing problems in logistic systems via reinforcement learning
Zong, Z., Wang, H., Wang, J., Zheng, M., and Li, Y · 2020
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Machine learning for combinatorial optimization: a methodological tour d’horizon
Bengio, Y., Lodi, A., and Prouvost, A · 2021
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Optimized path planning for electric vehicle routing and charging station navigation systems
Elgarej, M., Khalifa, M., and Youssfi, M · 2021
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Generalize a small pre-trained model to arbitrarily large tsp instances
Fu, Z.-H., Qiu, K.-B., and Zha, H · 2021
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Efficient active search for combinatorial optimization problems
Hottung, A., Kwon, Y.-D., and Tierney, K · 2021
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Learning collaborative policies to solve np-hard routing problems
Kim, M., Park, J., et al · 2021
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Vidal, T · 2022
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Select and optimize: Learning to aolve large-scale tsp instances
Cheng, H., Zheng, H., Cong, Y., Jiang, W., and Pu, S · 2023
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BQ-NCO: Bisimulation quotienting for efficient neural combinatorial optimization
Drakulic, D., Michel, S., Mai, F., Sors, A., and Andreoli, J.-M · 2023
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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
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Neural combinatorial optimization with heavy decoder: Toward large scale generalization
Luo, F., Lin, X., Liu, F., Zhang, Q., and Wang, Z · 2023
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H-tsp: Hierarchically solving the large-scale traveling salesman problem
Pan, X., Jin, Y., Ding, Y., Feng, M., Zhao, L., Song, L., and Bian, J · 2023
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DIFUSCO: Graph-based diffusion solvers for combinatorial optimization
Sun, Z. and Yang, Y · 2023
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Glop: Learning global partition and local construction for solving large-scale routing problems in real-time
Ye, H., Wang, J., Liang, H., Cao, Z., Li, Y., and Li, F · 2024
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