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Advances in Neural Information Processing Systems, Vol. 36 (2024)."},{"key":"e_1_3_2_2_52_1","volume-title":"International Conference on Learning Representations.","author":"Li Yang","year":"2025","unstructured":"Yang Li, Jiale Ma, Wenzheng Pan, Runzhong Wang, Haoyu Geng, Nianzu Yang, and Junchi Yan. 2025. Streamlining the Design Space of ML4TSP Suggests Principles for Learning and Search. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_53_1","volume-title":"Ray rllib: A composable and scalable reinforcement learning library. arXiv preprint arXiv:1712.09381","author":"Liang Eric","year":"2017","unstructured":"Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Joseph Gonzalez, Ken Goldberg, and Ion Stoica. 2017. Ray rllib: A composable and scalable reinforcement learning library. arXiv preprint arXiv:1712.09381, Vol. 85 (2017)."},{"key":"e_1_3_2_2_54_1","volume-title":"CVRPLIB: Capacitated Vehicle Routing Problem Library","author":"Lima Ivan","year":"2014","unstructured":"Ivan Lima, Eduardo Uchoa, Diego Pecin, Artur Pessoa, Marcus Poggi, Thibaut Vidal, Anand Subramanian, Richard W, Daniel Oliveira, and Eduardo Queiroga. 2014. CVRPLIB: Capacitated Vehicle Routing Problem Library. http:\/\/vrp.galgos.inf.puc-rio.br\/index.php\/en\/ Last checked on October 6, 2024."},{"key":"e_1_3_2_2_55_1","unstructured":"Jeffrey T Linderoth Andrea Lodi et al. 2010. MILP software. Wiley encyclopedia of operations research and management science Vol. 5 (2010) 3239-3248."},{"key":"e_1_3_2_2_56_1","volume-title":"Awesome Machine Learning for Combinatorial Optimization. https:\/\/github.com\/Thinklab-SJTU\/awesome-ml4co Accessed","author":"Liu Chang","year":"2025","unstructured":"Chang Liu, Runzhong Wang, Jiayi Zhang, Zelin Zhao, Haoyu Geng, Tianzhe Wang, Wenxuan Guo, Wenjie Wu, Nianzu Yang, Ziao Guo, Yang Li, Hao Xiong, and Junchi Yan. 2025. Awesome Machine Learning for Combinatorial Optimization. https:\/\/github.com\/Thinklab-SJTU\/awesome-ml4co Accessed: February 23, 2025."},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3672040"},{"key":"e_1_3_2_2_58_1","volume-title":"Advances in Neural Information Processing Systems","volume":"36","author":"Luo Fu","year":"2024","unstructured":"Fu Luo, Xi Lin, Fei Liu, Qingfu Zhang, and Zhenkun Wang. 2024. Neural combinatorial optimization with heavy decoder: Toward large scale generalization. Advances in Neural Information Processing Systems, Vol. 36 (2024)."},{"key":"e_1_3_2_2_59_1","volume-title":"Advances in Neural Information Processing Systems","volume":"36","author":"Ma Yining","year":"2024","unstructured":"Yining Ma, Zhiguang Cao, and Yeow Meng Chee. 2024. Learning to search feasible and infeasible regions of routing problems with flexible neural k-opt. Advances in Neural Information Processing Systems, Vol. 36 (2024)."},{"key":"e_1_3_2_2_60_1","unstructured":"Yining Ma Jingwen Li Zhiguang Cao Wen Song Hongliang Guo Yuejiao Gong and Yeow Meng Chee. 2022. Efficient Neural Neighborhood Search for Pickup and Delivery Problems. arXiv preprint arXiv:2204.11399(2022)."},{"key":"e_1_3_2_2_61_1","volume-title":"Advances in Neural Information Processing Systems","volume":"34","author":"Ma Yining","year":"2021","unstructured":"Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, and Jing Tang. 2021. Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer. Advances in Neural Information Processing Systems, Vol. 34 (2021)."},{"key":"e_1_3_2_2_62_1","volume-title":"Handbook of heuristics","author":"Mart Rafael","unstructured":"Rafael Mart, Panos M Pardalos, and Mauricio GC Resende. 2018. Handbook of heuristics. Springer Publishing Company, Incorporated."},{"key":"e_1_3_2_2_63_1","unstructured":"Yimeng Min Yiwei Bai and Carla P Gomes. 2023. Unsupervised Learning for Solving the Travelling Salesman Problem. In Neural Information Processing Systems."},{"key":"e_1_3_2_2_64_1","unstructured":"Vincent Moens. 2023. TensorDict: your PyTorch universal data carrier. https:\/\/github.com\/pytorch-labs\/tensordict"},{"key":"e_1_3_2_2_65_1","volume-title":"Reinforcement learning for solving the vehicle routing problem. Advances in neural information processing systems","author":"Nazari Mohammadreza","year":"2018","unstructured":"Mohammadreza Nazari, Afshin Oroojlooy, Lawrence Snyder, and Martin Tak\u00e1c. 2018. Reinforcement learning for solving the vehicle routing problem. Advances in neural information processing systems, Vol. 31 (2018)."},{"key":"e_1_3_2_2_66_1","first-page":"1","article-title":"Versatile Genetic Algorithm-Bayesian Optimization (GA-BO) Bi-Level Optimization for Decoupling Capacitor Placement. In 2023 IEEE 32nd Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS)","author":"Park Hyunah","year":"2023","unstructured":"Hyunah Park, Haeyeon Kim, Hyunwoo Kim, Joonsang Park, Seonguk Choi, Jihun Kim, Keeyoung Son, Haeseok Suh, Taesoo Kim, Jungmin Ahn, et al., 2023. Versatile Genetic Algorithm-Bayesian Optimization (GA-BO) Bi-Level Optimization for Decoupling Capacitor Placement. In 2023 IEEE 32nd Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS). IEEE, 1-3.","journal-title":"IEEE"},{"key":"e_1_3_2_2_67_1","unstructured":"Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga et al. 2019. PyTorch: An imperative style high-performance deep learning library. Advances in neural information processing systems Vol. 32 (2019)."},{"key":"e_1_3_2_2_68_1","unstructured":"Laurent Perron and Vincent Furnon. 2023. OR-Tools. https:\/\/developers.google.com\/optimization\/"},{"key":"e_1_3_2_2_69_1","volume-title":"Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers. In Learning Meets Combinatorial Algorithms at NeurIPS2020. https:\/\/openreview.net\/forum?id=IVc9hqgibyB","author":"Prouvost Antoine","year":"2020","unstructured":"Antoine Prouvost, Justin Dumouchelle, Lara Scavuzzo, Maxime Gasse, Didier Ch\u00e9telat, and Andrea Lodi. 2020. Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers. In Learning Meets Combinatorial Algorithms at NeurIPS2020. https:\/\/openreview.net\/forum?id=IVc9hqgibyB"},{"key":"e_1_3_2_2_70_1","first-page":"1","article-title":"Stable-Baselines3: Reliable Reinforcement Learning Implementations","volume":"22","author":"Raffin Antonin","year":"2021","unstructured":"Antonin Raffin, Ashley Hill, Adam Gleave, Anssi Kanervisto, Maximilian Ernestus, and Noah Dormann. 2021. Stable-Baselines3: Reliable Reinforcement Learning Implementations. Journal of Machine Learning Research, Vol. 22, 268 (2021), 1-8. http:\/\/jmlr.org\/papers\/v22\/20-1364.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_71_1","doi-asserted-by":"publisher","DOI":"10.1057\/jors.1982.184"},{"key":"e_1_3_2_2_72_1","volume-title":"TSPLIB-A traveling salesman problem library. ORSA journal on computing","author":"Reinelt Gerhard","year":"1991","unstructured":"Gerhard Reinelt. 1991. TSPLIB-A traveling salesman problem library. ORSA journal on computing, Vol. 3, 4 (1991), 376-384."},{"key":"e_1_3_2_2_73_1","volume-title":"The general pickup and delivery problem. Transportation science","author":"Savelsbergh Martin WP","year":"1995","unstructured":"Martin WP Savelsbergh and Marc Sol. 1995. The general pickup and delivery problem. Transportation science, Vol. 29, 1 (1995), 17-29."},{"key":"e_1_3_2_2_74_1","unstructured":"John Schulman Filip Wolski Prafulla Dhariwal Alec Radford and Oleg Klimov. 2017. Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347(2017)."},{"key":"e_1_3_2_2_75_1","first-page":"354","volume-title":"Nature","volume":"550","author":"Silver David","year":"2017","unstructured":"David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al., 2017. Mastering the game of Go without human knowledge. Nature, Vol. 550, 7676 (2017), 354-359."},{"key":"e_1_3_2_2_76_1","first-page":"20012","article-title":"A general large neighborhood search framework for solving integer linear programs","volume":"33","author":"Song Jialin","year":"2020","unstructured":"Jialin Song, Yisong Yue, Bistra Dilkina, et al., 2020. A general large neighborhood search framework for solving integer linear programs. Advances in Neural Information Processing Systems, Vol. 33 (2020), 20012-20023.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_77_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3189725"},{"key":"e_1_3_2_2_78_1","first-page":"3706","article-title":"DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization","volume":"36","author":"Sun Zhiqing","year":"2023","unstructured":"Zhiqing Sun and Yiming Yang. 2023. DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization. In Advances in Neural Information Processing Systems, Vol. 36. 3706-3731.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_79_1","volume-title":"Policy gradient methods for reinforcement learning with function approximation. Advances in neural information processing systems","author":"Sutton Richard S","year":"1999","unstructured":"Richard S Sutton, David McAllester, Satinder Singh, and Yishay Mansour. 1999. Policy gradient methods for reinforcement learning with function approximation. Advances in neural information processing systems, Vol. 12 (1999)."},{"key":"e_1_3_2_2_80_1","volume-title":"Routing Arena: A Benchmark Suite for Neural Routing Solvers. arXiv preprint arXiv:2310.04140(2023).","author":"Thyssens Daniela","year":"2023","unstructured":"Daniela Thyssens, Tim Dernedde, Jonas K Falkner, and Lars Schmidt-Thieme. 2023. Routing Arena: A Benchmark Suite for Neural Routing Solvers. arXiv preprint arXiv:2310.04140(2023)."},{"key":"e_1_3_2_2_81_1","volume-title":"Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971(2023).","author":"Touvron Hugo","year":"2023","unstructured":"Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth\u00e9e Lacroix, Baptiste Rozi\u00e8re, Naman Goyal, Eric Hambro, Faisal Azhar, et al., 2023. Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971(2023)."},{"key":"e_1_3_2_2_82_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2021.105643"},{"key":"e_1_3_2_2_83_1","first-page":"2692","article-title":"Pointer Networks","volume":"28","author":"Vinyals Oriol","year":"2015","unstructured":"Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly. 2015. Pointer Networks. In Advances in Neural Information Processing Systems, Vol. 28. 2692-2700.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_84_1","volume-title":"RLOR: A Flexible Framework of Deep Reinforcement Learning for Operation Research. arXiv preprint arXiv:2303.13117(2023).","author":"Wan Ching Pui","year":"2023","unstructured":"Ching Pui Wan, Tung Li, and Jason Min Wang. 2023. RLOR: A Flexible Framework of Deep Reinforcement Learning for Operation Research. arXiv preprint arXiv:2303.13117(2023)."},{"key":"e_1_3_2_2_85_1","first-page":"1","article-title":"Tianshou: A highly modularized deep reinforcement learning library","volume":"23","author":"Weng Jiayi","year":"2022","unstructured":"Jiayi Weng, Huayu Chen, Dong Yan, Kaichao You, Alexis Duburcq, Minghao Zhang, Yi Su, Hang Su, and Jun Zhu. 2022. Tianshou: A highly modularized deep reinforcement learning library. Journal of Machine Learning Research, Vol. 23, 267 (2022), 1-6.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_86_1","doi-asserted-by":"crossref","unstructured":"Niels A Wouda Leon Lan and Wouter Kool. 2024. PyVRP: A high-performance VRP solver package. INFORMS Journal on Computing(2024).","DOI":"10.1287\/ijoc.2023.0055"},{"key":"e_1_3_2_2_87_1","volume-title":"Learning improvement heuristics for solving routing problems","author":"Wu Yaoxin","year":"2021","unstructured":"Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, and Andrew Lim. 2021. Learning improvement heuristics for solving routing problems. IEEE transactions on neural networks and learning systems, Vol. 33, 9 (2021), 5057-5069."},{"key":"e_1_3_2_2_88_1","unstructured":"Omry Yadan. 2019. Hydra - A framework for elegantly configuring complex applications. Github. https:\/\/github.com\/facebookresearch\/hydra"},{"key":"e_1_3_2_2_89_1","unstructured":"Haoran Ye Jiarui Wang Zhiguang Cao Helan Liang and Yong Li. 2023. DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization. arXiv preprint arXiv:2309.14032(2023)."},{"key":"e_1_3_2_2_90_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i18.30009"},{"key":"e_1_3_2_2_91_1","volume-title":"Puay Siew Tan, and Xu Chi","author":"Zhang Cong","year":"2020","unstructured":"Cong Zhang, Wen Song, Zhiguang Cao, Jie Zhang, Puay Siew Tan, and Xu Chi. 2020. Learning to dispatch for job shop scheduling via deep reinforcement learning. Advances in Neural Information Processing Systems(2020)."},{"key":"e_1_3_2_2_92_1","first-page":"11952","volume-title":"Levine(Eds.)","volume":"36","author":"Zhang Dinghuai","year":"2023","unstructured":"Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C Courville, Yoshua Bengio, and Ling Pan. 2023. Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. In Advances in Neural Information Processing Systems, A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, and S. Levine(Eds.), Vol. 36. Curran Associates, Inc., 11952-11969."},{"key":"e_1_3_2_2_93_1","volume-title":"MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts. In International Conference on Machine Learning. endthebibl","author":"Zhou Jianan","year":"2024","unstructured":"Jianan Zhou, Zhiguang Cao, Yaoxin Wu, Wen Song, Yining Ma, Jie Zhang, and Chi Xu. 2024. MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts. 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