{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T07:16:21Z","timestamp":1781248581033,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":36,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:00:00Z","timestamp":1597881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,8,23]]},"DOI":"10.1145\/3394486.3403356","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T23:03:59Z","timestamp":1597964639000},"page":"3054-3063","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":78,"title":["Efficiently Solving the Practical Vehicle Routing Problem"],"prefix":"10.1145","author":[{"given":"Lu","family":"Duan","sequence":"first","affiliation":[{"name":"Zhejiang Cainiao Supply Chain Management Co. Ltd, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Zhan","sequence":"additional","affiliation":[{"name":"Zhejiang Cainiao Supply Chain Management Co. Ltd, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoyuan","family":"Hu","sequence":"additional","affiliation":[{"name":"Zhejiang Cainiao Supply Chain Management Co. Ltd, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Gong","sequence":"additional","affiliation":[{"name":"Alibaba Group, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiangwen","family":"Wei","sequence":"additional","affiliation":[{"name":"Zhejiang Cainiao Supply Chain Management Co. Ltd, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Zhejiang Cainiao Supply Chain Management Co. Ltd, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinghui","family":"Xu","sequence":"additional","affiliation":[{"name":"Zhejiang Cainiao Supply Chain Management Co. Ltd, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Jamie Ryan Kiros, and Geoffrey E Hinton","author":"Ba Jimmy Lei","year":"2016","unstructured":"Jimmy Lei Ba , Jamie Ryan Kiros, and Geoffrey E Hinton . 2016 . Layer normalization. arXiv preprint arXiv:1607.06450 (2016). Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016. Layer normalization. arXiv preprint arXiv:1607.06450 (2016)."},{"key":"e_1_3_2_1_2_1","volume-title":"Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473","author":"Bahdanau Dzmitry","year":"2014","unstructured":"Dzmitry Bahdanau , Kyunghyun Cho , and Yoshua Bengio . 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 ( 2014 ). Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)."},{"key":"e_1_3_2_1_3_1","volume-title":"Neural combinatorial optimization with reinforcement learning. arXiv preprint arXiv:1611.09940","author":"Bello Irwan","year":"2016","unstructured":"Irwan Bello , Hieu Pham , Quoc V. Le , Mohammad Norouzi , and Samy Bengio . 2016. Neural combinatorial optimization with reinforcement learning. arXiv preprint arXiv:1611.09940 ( 2016 ). Irwan Bello, Hieu Pham, Quoc V. Le, Mohammad Norouzi, and Samy Bengio. 2016. Neural combinatorial optimization with reinforcement learning. arXiv preprint arXiv:1611.09940 (2016)."},{"key":"e_1_3_2_1_4_1","volume-title":"Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio.","author":"Cho Kyunghyun","year":"2014","unstructured":"Kyunghyun Cho , Bart Van Merri\u00ebnboer , Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 . Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014). Kyunghyun Cho, Bart Van Merri\u00ebnboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014)."},{"key":"e_1_3_2_1_5_1","volume-title":"International Conference on Machine Learning. 2702--2711","author":"Dai Hanjun","year":"2016","unstructured":"Hanjun Dai , Bo Dai , and Le Song . 2016 . Discriminative embeddings of latent variable models for structured data . In International Conference on Machine Learning. 2702--2711 . Hanjun Dai, Bo Dai, and Le Song. 2016. Discriminative embeddings of latent variable models for structured data. In International Conference on Machine Learning. 2702--2711."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93031-2_12"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-005-0644-x"},{"key":"e_1_3_2_1_8_1","volume-title":"Graves","author":"Gavish Bezalel","year":"1978","unstructured":"Bezalel Gavish and Stephen C . Graves . 1978 . The travelling salesman problem and related problems. (1978). Bezalel Gavish and Stephen C. Graves. 1978. The travelling salesman problem and related problems. (1978)."},{"key":"e_1_3_2_1_9_1","volume-title":"Wasil","author":"Golden Bruce L.","year":"2008","unstructured":"Bruce L. Golden , Subramanian Raghavan , and Edward A . Wasil . 2008 . The vehicle routing problem: latest advances and new challenges. Vol. 43 . Springer Science & Business Media . Bruce L. Golden, Subramanian Raghavan, and Edward A. Wasil. 2008. The vehicle routing problem: latest advances and new challenges. Vol. 43. Springer Science & Business Media."},{"key":"e_1_3_2_1_10_1","unstructured":"Google. 2019. OR-Tools . https:\/\/developers.google.com\/optimization  Google. 2019. OR-Tools . https:\/\/developers.google.com\/optimization"},{"key":"e_1_3_2_1_11_1","unstructured":"Gurobi Optimization LLC. 2019. Gurobi Optimizer Reference Manual. http:\/\/www.gurobi.com  Gurobi Optimization LLC. 2019. Gurobi Optimizer Reference Manual. http:\/\/www.gurobi.com"},{"key":"e_1_3_2_1_12_1","unstructured":"Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Advances in Neural Information Processing Systems. 1024--1034.  Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Advances in Neural Information Processing Systems. 1024--1034."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_14_1","volume-title":"An extension of the Lin-Kernighan-Helsgaun TSP solver for constrained traveling salesman and vehicle routing problems","author":"Helsgaun Keld","year":"2017","unstructured":"Keld Helsgaun . 2017. An extension of the Lin-Kernighan-Helsgaun TSP solver for constrained traveling salesman and vehicle routing problems . Roskilde : Roskilde University ( 2017 ). Keld Helsgaun. 2017. An extension of the Lin-Kernighan-Helsgaun TSP solver for constrained traveling salesman and vehicle routing problems. Roskilde: Roskilde University (2017)."},{"key":"e_1_3_2_1_15_1","volume-title":"Long short-term memory. Neural computation","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber . 1997. Long short-term memory. Neural computation , Vol. 9 , 8 ( 1997 ), 1735--1780. Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural computation, Vol. 9, 8 (1997), 1735--1780."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2909109"},{"key":"e_1_3_2_1_17_1","volume-title":"An efficient graph convolutional network technique for the travelling salesman problem. arXiv preprint arXiv:1906.01227","author":"Joshi Chaitanya K","year":"2019","unstructured":"Chaitanya K Joshi , Thomas Laurent , and Xavier Bresson . 2019. An efficient graph convolutional network technique for the travelling salesman problem. arXiv preprint arXiv:1906.01227 ( 2019 ). Chaitanya K Joshi, Thomas Laurent, and Xavier Bresson. 2019. An efficient graph convolutional network technique for the travelling salesman problem. arXiv preprint arXiv:1906.01227 (2019)."},{"key":"e_1_3_2_1_18_1","volume-title":"Learning the multiple traveling salesmen problem with permutation invariant pooling networks. arXiv preprint arXiv:1803.09621","author":"Kaempfer Yoav","year":"2018","unstructured":"Yoav Kaempfer and Lior Wolf . 2018. Learning the multiple traveling salesmen problem with permutation invariant pooling networks. arXiv preprint arXiv:1803.09621 ( 2018 ). Yoav Kaempfer and Lior Wolf. 2018. Learning the multiple traveling salesmen problem with permutation invariant pooling networks. arXiv preprint arXiv:1803.09621 (2018)."},{"key":"e_1_3_2_1_19_1","unstructured":"Elias Khalil Hanjun Dai Yuyu Zhang Bistra Dilkina and Le Song. 2017. Learning combinatorial optimization algorithms over graphs. In Advances in Neural Information Processing Systems. 6348--6358.  Elias Khalil Hanjun Dai Yuyu Zhang Bistra Dilkina and Le Song. 2017. Learning combinatorial optimization algorithms over graphs. In Advances in Neural Information Processing Systems. 6348--6358."},{"key":"e_1_3_2_1_20_1","unstructured":"Vijay R Konda and John N Tsitsiklis. 2000. Actor-critic algorithms. In Advances in Neural Information Processing Systems. 1008--1014.  Vijay R Konda and John N Tsitsiklis. 2000. Actor-critic algorithms. In Advances in Neural Information Processing Systems. 1008--1014."},{"key":"e_1_3_2_1_21_1","volume-title":"learn to solve routing problems! In International Conference on Learning Representations","author":"Kool Wouter","year":"2019","unstructured":"Wouter Kool , Herke van Hoof , and Max Welling . 2019. Attention , learn to solve routing problems! In International Conference on Learning Representations ( 2019 ). Wouter Kool, Herke van Hoof, and Max Welling. 2019. Attention, learn to solve routing problems! In International Conference on Learning Representations (2019)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/0377-2217(92)90192-C"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1475-3995.2000.tb00200.x"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.5555\/1139300.1668400"},{"key":"e_1_3_2_1_25_1","volume-title":"Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602","author":"Mnih Volodymyr","year":"2013","unstructured":"Volodymyr Mnih , Koray Kavukcuoglu , David Silver , Alex Graves , Ioannis Antonoglou , Daan Wierstra , and Martin Riedmiller . 2013. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602 ( 2013 ). Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller. 2013. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602 (2013)."},{"key":"e_1_3_2_1_26_1","unstructured":"Mohammadreza Nazari Afshin Oroojlooy Lawrence Snyder and Martin Tak\u00e1c. 2018. Reinforcement learning for solving the vehicle routing problem. In Advances in Neural Information Processing Systems. 9839--9849.  Mohammadreza Nazari Afshin Oroojlooy Lawrence Snyder and Martin Tak\u00e1c. 2018. Reinforcement learning for solving the vehicle routing problem. In Advances in Neural Information Processing Systems. 9839--9849."},{"key":"e_1_3_2_1_27_1","first-page":"22","article-title":"A note on learning algorithms for quadratic assignment with graph neural networks","volume":"1050","author":"Nowak Alex","year":"2017","unstructured":"Alex Nowak , Soledad Villar , Afonso S Bandeira , and Joan Bruna . 2017 . A note on learning algorithms for quadratic assignment with graph neural networks . Stat , Vol. 1050 (2017), 22 . Alex Nowak, Soledad Villar, Afonso S Bandeira, and Joan Bruna. 2017. A note on learning algorithms for quadratic assignment with graph neural networks. Stat, Vol. 1050 (2017), 22.","journal-title":"Stat"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-002-0323-0"},{"key":"e_1_3_2_1_29_1","volume-title":"Reinforcement learning: An introduction","author":"Sutton Richard S","unstructured":"Richard S Sutton and Andrew G Barto . 2018. Reinforcement learning: An introduction . MIT press . Richard S Sutton and Andrew G Barto. 2018. Reinforcement learning: An introduction .MIT press."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"Paolo Toth and Daniele Vigo. 2002. The vehicle routing problem .SIAM.  Paolo Toth and Daniele Vigo. 2002. The vehicle routing problem .SIAM.","DOI":"10.1137\/1.9780898718515"},{"key":"e_1_3_2_1_31_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems. 5998--6008.  Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems. 5998--6008."},{"key":"e_1_3_2_1_32_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Petar Velivc","year":"2017","unstructured":"Petar Velivc kovi\u0107, Guillem Cucurull , Arantxa Casanova , Adriana Romero , Pietro Lio , and Yoshua Bengio . 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 ( 2017 ). Petar Velivc kovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_1_33_1","unstructured":"Oriol Vinyals Meire Fortunato and Navdeep Jaitly. 2015. Pointer networks. In Advances in neural information processing systems. 2692--2700.  Oriol Vinyals Meire Fortunato and Navdeep Jaitly. 2015. Pointer networks. In Advances in neural information processing systems. 2692--2700."},{"key":"e_1_3_2_1_34_1","volume-title":"et almbox","author":"Wu Yonghui","year":"2016","unstructured":"Yonghui Wu , Mike Schuster , Zhifeng Chen , Quoc V Le , Mohammad Norouzi , Wolfgang Macherey , Maxim Krikun , Yuan Cao , Qin Gao , Klaus Macherey , et almbox . 2016 . Google's neural machine translation system: Bridging the gap between human and machine translation. arXiv preprint arXiv:1609.08144 (2016). Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et almbox. 2016. Google's neural machine translation system: Bridging the gap between human and machine translation. arXiv preprint arXiv:1609.08144 (2016)."},{"key":"e_1_3_2_1_35_1","volume-title":"How powerful are graph neural networks? arXiv preprint arXiv:1810.00826","author":"Xu Keyulu","year":"2018","unstructured":"Keyulu Xu , Weihua Hu , Jure Leskovec , and Stefanie Jegelka . 2018a. How powerful are graph neural networks? arXiv preprint arXiv:1810.00826 ( 2018 ). Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2018a. How powerful are graph neural networks? arXiv preprint arXiv:1810.00826 (2018)."},{"key":"e_1_3_2_1_36_1","volume-title":"Representation learning on graphs with jumping knowledge networks. arXiv preprint arXiv:1806.03536","author":"Xu Keyulu","year":"2018","unstructured":"Keyulu Xu , Chengtao Li , Yonglong Tian , Tomohiro Sonobe , Ken-ichi Kawarabayashi, and Stefanie Jegelka . 2018b. Representation learning on graphs with jumping knowledge networks. arXiv preprint arXiv:1806.03536 ( 2018 ). Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, and Stefanie Jegelka. 2018b. Representation learning on graphs with jumping knowledge networks. arXiv preprint arXiv:1806.03536 (2018)."}],"event":{"name":"KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event CA USA","acronym":"KDD '20","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403356","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394486.3403356","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:29Z","timestamp":1750195889000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403356"}},"subtitle":["A Novel Joint Learning Approach"],"short-title":[],"issued":{"date-parts":[[2020,8,20]]},"references-count":36,"alternative-id":["10.1145\/3394486.3403356","10.1145\/3394486"],"URL":"https:\/\/doi.org\/10.1145\/3394486.3403356","relation":{},"subject":[],"published":{"date-parts":[[2020,8,20]]},"assertion":[{"value":"2020-08-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}