{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:28:23Z","timestamp":1775143703077,"version":"3.50.1"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Agency for Science Technology and Research Career Development Fund","award":["222D8235"],"award-info":[{"award-number":["222D8235"]}]},{"name":"Agency for Science Technology and Research Career Development Fund","award":["C222812027"],"award-info":[{"award-number":["C222812027"]}]},{"DOI":"10.13039\/501100001471","name":"IEO Decentralized GAP Project of Continuous Last-Mile Logistics (CLML) at the Singapore Institute of Manufacturing Technology","doi-asserted-by":"publisher","award":["I22D1AG003"],"award-info":[{"award-number":["I22D1AG003"]}],"id":[{"id":"10.13039\/501100001471","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001475","name":"Rapid-Rich Object Search (ROSE) Laboratory, Nanyang Technological University, Singapore","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001475","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Education, Singapore, under its Academic Research Fund Tier 1","award":["RG61\/22"],"award-info":[{"award-number":["RG61\/22"]}]},{"name":"Start-Up Grant"},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62102228"],"award-info":[{"award-number":["62102228"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Shandong Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["ZR2021QF063"],"award-info":[{"award-number":["ZR2021QF063"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1109\/tits.2022.3207011","type":"journal-article","created":{"date-parts":[[2022,9,23]],"date-time":"2022-09-23T20:01:25Z","timestamp":1663963285000},"page":"1325-1336","source":"Crossref","is-referenced-by-count":44,"title":["Learning to Solve Multiple-TSP With Time Window and Rejections via Deep Reinforcement Learning"],"prefix":"10.1109","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0034-460X","authenticated-orcid":false,"given":"Rongkai","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore"}]},{"given":"Cong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4499-759X","authenticated-orcid":false,"given":"Zhiguang","family":"Cao","sequence":"additional","affiliation":[{"name":"Singapore Institute of Manufacturing Technology (SIMTech), Agency for Science Technology and Research (A*STAR), Fusionopolis, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7624-1861","authenticated-orcid":false,"given":"Wen","family":"Song","sequence":"additional","affiliation":[{"name":"Institute of Marine Science and Technology, Shandong University, Qingdao, China"}]},{"given":"Puay Siew","family":"Tan","sequence":"additional","affiliation":[{"name":"Singapore Institute of Manufacturing Technology (SIMTech), Agency for Science Technology and Research (A*STAR), Fusionopolis, Singapore"}]},{"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6874-6453","authenticated-orcid":false,"given":"Bihan","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore"}]},{"given":"Justin","family":"Dauwels","sequence":"additional","affiliation":[{"name":"Department of Microelectronics, Faculty EEMCS, Technische Universiteit Delft, Delft, The Netherlands"}]}],"member":"263","reference":[{"key":"ref1","first-page":"539","article-title":"Combinatorial optimization with graph convolutional networks and guided tree search","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref2","first-page":"7992","article-title":"Learning local search heuristics for Boolean satisfiability","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yolcu"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3056120"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i8.16916"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3031409"},{"key":"ref6","first-page":"1","article-title":"Neurolkh: Combining deep learning model with Lin-Kernighan\u2013Helsgaun heuristic for solving the traveling salesman problem","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Xin"},{"key":"ref7","article-title":"Dynamic partial removal: A neural network heuristic for large neighborhood search","author":"Chen","year":"2020","journal-title":"arXiv:2005.09330"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3003163"},{"key":"ref9","article-title":"Learning the multiple traveling salesmen problem with permutation invariant pooling networks","author":"Kaempfer","year":"2018","journal-title":"arXiv:1803.09621"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106244"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3111082"},{"key":"ref12","first-page":"2692","article-title":"Pointer networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Vinyals"},{"key":"ref13","first-page":"9839","article-title":"Reinforcement learning for solving the vehicle routing problem","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Nazari"},{"key":"ref14","first-page":"5998","article-title":"Attention is all you need","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Vaswani"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93031-2_12"},{"key":"ref16","first-page":"1","article-title":"Attention, learn to solve routing problems!","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kool"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3068828"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i8.16916"},{"key":"ref19","volume-title":"Or-Tools","author":"Perron","year":"2019"},{"key":"ref20","article-title":"Combinatorial optimization by graph pointer networks and hierarchical reinforcement learning","author":"Ma","year":"2019","journal-title":"arXiv:1911.04936"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1287\/opre.31.5.938"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207026"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/0377-2217(95)00185-9"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16484"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.1998.712192"},{"key":"ref26","first-page":"1","article-title":"How powerful are graph neural networks?","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Xu"},{"key":"ref27","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ioffe"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/bf00992696"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3443467.3443899"},{"key":"ref30","first-page":"8026","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Paszke"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107770"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.3390\/info10010007"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-016-9476-8"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2018.02.001"},{"key":"ref35","volume-title":"YPEA: Yarpiz evolutionary algorithms","author":"Heris","year":"2019"},{"key":"ref36","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/10026638\/09901466.pdf?arnumber=9901466","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T21:57:03Z","timestamp":1705960623000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9901466\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1]]},"references-count":36,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tits.2022.3207011","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1]]}}}