{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T12:54:33Z","timestamp":1766408073151,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030859275"},{"type":"electronic","value":"9783030859282"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-85928-2_23","type":"book-chapter","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T12:12:16Z","timestamp":1631103136000},"page":"288-300","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Effective Cross-Region Courier-Displacement for Instant Delivery via Reinforcement Learning"],"prefix":"10.1007","author":[{"given":"Shijie","family":"Hu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baoshen","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolei","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,2]]},"reference":[{"key":"23_CR1","unstructured":"Consulting statistics (2020). http:\/\/www.bigdata-research.cn\/content\/201912\/1026.html. Accessed 29 Jan 2020"},{"key":"23_CR2","unstructured":"Amazon-Prime-Now: Amazon prime now (2020). https:\/\/primenow.amazon.com\/. Accessed 20 Apr 2020"},{"key":"23_CR3","doi-asserted-by":"publisher","unstructured":"Chen, J., et al.: A hybrid differential evolution algorithm for the online meal delivery problem. In: 2020 IEEE Congress on Evolutionary Computation (CEC), pp. 1\u20138 (2020). https:\/\/doi.org\/10.1109\/CEC48606.2020.9185792","DOI":"10.1109\/CEC48606.2020.9185792"},{"key":"23_CR4","unstructured":"Contardo, C., Morency, C., Rousseau, L.: Balancing a dynamic public bike-sharing system. CIRRELT (2012)"},{"key":"23_CR5","unstructured":"Deliveroo: Deliveroo (2020). https:\/\/deliveroo.co.uk. Accessed 20 Apr 2020"},{"key":"23_CR6","unstructured":"DoorDash: Doordash (2020). https:\/\/www.doordash.com\/en-US. Accessed 3 May 2020"},{"key":"23_CR7","unstructured":"Ele.me: Ele.me 2008. ele.me website (2020). http:\/\/www.ele.me\/. Accessed 29 Oct 2020"},{"key":"23_CR8","doi-asserted-by":"publisher","unstructured":"He, S., Shin, K.G.: Spatio-temporal capsule-based reinforcement learning for mobility-on-demand network coordination. In: The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13\u201317, 2019, pp. 2806\u20132813 (2019). https:\/\/doi.org\/10.1145\/3308558.3313401","DOI":"10.1145\/3308558.3313401"},{"key":"23_CR9","doi-asserted-by":"crossref","unstructured":"Ji, S., Zheng, Y., Wang, Z., Li, T.: Alleviating users\u2019 pain of waiting: Effective task grouping for online-to-offline food delivery services, pp. 773\u2013783 (2019)","DOI":"10.1145\/3308558.3313464"},{"key":"23_CR10","doi-asserted-by":"publisher","unstructured":"Lin, K., Zhao, R., Xu, Z., Zhou, J.: Efficient large-scale fleet management via multi-agent deep reinforcement learning. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & #38; Data Mining, pp. 1774\u20131783. KDD \u201918, ACM, New York, NY, USA (2018). https:\/\/doi.org\/10.1145\/3219819.3219993","DOI":"10.1145\/3219819.3219993"},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Liu, J., Sun, L., Chen, W., Xiong, H.: Rebalancing bike sharing systems: a multi-source data smart optimization. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1005\u20131014 (2016)","DOI":"10.1145\/2939672.2939776"},{"key":"23_CR12","doi-asserted-by":"crossref","unstructured":"Contardo, C., Morency, C., Rousseau, L.M.: Balancing a dynamic public bike-sharing system. RAIRO - Oper. Res. 45(1), 37\u201361 (2011)","DOI":"10.1051\/ro\/2011102"},{"key":"23_CR13","unstructured":"MeiTuan: Meituan (2021). https:\/\/www.meituan.com\/"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Oda, T., Joe-Wong, C.: Movi: a model-free approach to dynamic fleet management. In: IEEE International Conference on Computer Communications, vol. abs\/1804.04758, pp. 2708\u20132716 (2018)","DOI":"10.1109\/INFOCOM.2018.8485988"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Raviv, T., Michal, T., Forma, I.: Static repositioning in a bike-sharing system: models and solution approaches. EURO J. Transp. Logistics 2(3), 187\u2013229 (2013)","DOI":"10.1007\/s13676-012-0017-6"},{"key":"23_CR16","doi-asserted-by":"publisher","unstructured":"Ropke, S., Cordeau, J.F.: Branch and cut and price for the pickup and delivery problem with time windows. Transp. Sci. 43(3), 267\u2013286 (2009). https:\/\/doi.org\/10.1287\/trsc.1090.0272","DOI":"10.1287\/trsc.1090.0272"},{"key":"23_CR17","unstructured":"Ubereats: Ubereats (2020). https:\/\/www.ubereats.com\/hk. Accessed 20 Apr 2020"},{"key":"23_CR18","doi-asserted-by":"publisher","unstructured":"Wang, S., He, T., Zhang, D., Liu, Y., Son, H.S.: Towards efficient sharing: a usage balancing mechanism for bike sharing systems. In: The World Wide Web Conference, pp. 2011\u20132021. Association for Computing Machinery, New York, NY, USA (2019). https:\/\/doi.org\/10.1145\/3308558.3313441","DOI":"10.1145\/3308558.3313441"},{"key":"23_CR19","doi-asserted-by":"crossref","unstructured":"Xie, X., Zhang, F., Zhang, D.: Privatehunt: multi-source data-driven dispatching in for-hire vehicle systems. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 45:1\u201345:26 (2018)","DOI":"10.1145\/3191777"},{"key":"23_CR20","doi-asserted-by":"crossref","unstructured":"Yang, Z., Hu, J., Shu, Y., Cheng, P., Chen, J., Moscibroda, T.: Mobility modeling and prediction in bike-sharing systems. In: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services, pp. 165\u2013178 (2016)","DOI":"10.1145\/2906388.2906408"},{"key":"23_CR21","doi-asserted-by":"publisher","unstructured":"Zheng, J., et al.: A two-stage algorithm for fuzzy online order dispatching problem. In: 2020 IEEE Congress on Evolutionary Computation (CEC), pp. 1\u20138 (2020). https:\/\/doi.org\/10.1109\/CEC48606.2020.9185858","DOI":"10.1109\/CEC48606.2020.9185858"},{"key":"23_CR22","doi-asserted-by":"publisher","unstructured":"Zhou, Q., et al.: Two fast heuristics for online order dispatching. In: 2020 IEEE Congress on Evolutionary Computation (CEC), pp. 1\u20138 (2020). https:\/\/doi.org\/10.1109\/CEC48606.2020.9185791","DOI":"10.1109\/CEC48606.2020.9185791"}],"container-title":["Lecture Notes in Computer Science","Wireless Algorithms, Systems, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-85928-2_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T12:19:52Z","timestamp":1631103592000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-85928-2_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030859275","9783030859282"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-85928-2_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"2 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WASA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Wireless Algorithms, Systems, and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 June 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wasa2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wasa-conference.org\/WASA2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"315","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"103","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"57","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"33% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}