{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T10:00:44Z","timestamp":1755597644661,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":13,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819947546"},{"type":"electronic","value":"9789819947553"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-4755-3_4","type":"book-chapter","created":{"date-parts":[[2023,7,30]],"date-time":"2023-07-30T00:02:38Z","timestamp":1690675358000},"page":"37-46","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Real-Time Crowdsourced Delivery Optimization Considering Maximum Detour Distance"],"prefix":"10.1007","author":[{"given":"Xianlin","family":"Feng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nai-Kang","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Qian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang Sheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,30]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.tbs.2020.08.004","volume":"22","author":"H Buldeo Rai","year":"2021","unstructured":"Buldeo Rai, H., Verlinde, S., Macharis, C.: Who is interested in a crowdsourced last mile? A segmentation of attitudinal profiles. Travel Behav. Soc. 22, 22\u201331 (2021). https:\/\/doi.org\/10.1016\/j.tbs.2020.08.004","journal-title":"Travel Behav. Soc."},{"key":"4_CR2","series-title":"Topics in Regulatory Economics and Policy","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/978-3-319-46046-8_12","volume-title":"The Changing Postal and Delivery Sector","author":"C Borsenberger","year":"2017","unstructured":"Borsenberger, C.: The sharing economy and the \u201cUberization\u201d phenomenon: what impacts on the economy in general and for the delivery operators in particular? In: Crew, M., Parcu, P.L., Brennan, T. (eds.) The Changing Postal and Delivery Sector. TREP, pp. 191\u2013203. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-46046-8_12"},{"key":"4_CR3","doi-asserted-by":"publisher","first-page":"570","DOI":"10.1108\/IJPDLM-11-2017-0355","volume":"48","author":"V Carbone","year":"2018","unstructured":"Carbone, V., Rouquet, A., Roussat, C.: A typology of logistics at work in collaborative consumption. IJPDLM 48, 570\u2013585 (2018). https:\/\/doi.org\/10.1108\/IJPDLM-11-2017-0355","journal-title":"IJPDLM"},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1287\/mnsc.6.1.80","volume":"6","author":"GB Dantzig","year":"1959","unstructured":"Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manag. Sci. 6, 80\u201391 (1959). https:\/\/doi.org\/10.1287\/mnsc.6.1.80","journal-title":"Manag. Sci."},{"key":"4_CR5","doi-asserted-by":"publisher","first-page":"102139","DOI":"10.1016\/j.omega.2019.102139","volume":"98","author":"A Alnaggar","year":"2021","unstructured":"Alnaggar, A., Gzara, F., Bookbinder, J.H.: Crowdsourced delivery: a review of platforms and academic literature. Omega 98, 102139 (2021). https:\/\/doi.org\/10.1016\/j.omega.2019.102139","journal-title":"Omega"},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"To, H., Shahabi, C., Kazemi, L.: A server-assigned spatial crowdsourcing framework, vol. 1 (2015)","DOI":"10.1145\/2729713"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Deng, D., Shahabi, C., Demiryurek, U.: Maximizing the number of worker\u2019s self-selected tasks in spatial crowdsourcing. In: Knoblock, C.A., Schneider, M., Kr\u00f6ger, P., Krumm, J., Widmayer, P. (eds.) 21st SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2013, Orlando, FL, USA, 5\u20138 November 2013, pp. 314\u2013323. ACM (2013)","DOI":"10.1145\/2525314.2525370"},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Deng, D., Shahabi, C., Zhu, L.: Task matching and scheduling for multiple workers in spatial crowdsourcing. In: Bao, J., et al. (eds.) Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, Bellevue, WA, USA, 3\u20136 November 2015, pp. 21:1\u201321:10. ACM (2015)","DOI":"10.1145\/2820783.2820831"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Asghari, M., Shahabi, C.: On on-line task assignment in spatial crowdsourcing. In: Nie, J.-Y., et al. (eds.) 2017 IEEE International Conference on Big Data (IEEE BigData 2017), Boston, MA, USA, 11\u201314 December 2017, pp. 395\u2013404. IEEE Computer Society (2017)","DOI":"10.1109\/BigData.2017.8257951"},{"key":"4_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/978-3-319-22363-6_8","volume-title":"Advances in Spatial and Temporal Databases","author":"Y Li","year":"2015","unstructured":"Li, Y., Yiu, M.L., Xu, W.: Oriented online route recommendation for spatial crowdsourcing task workers. In: Claramunt, C., et al. (eds.) SSTD 2015. LNCS, vol. 9239, pp. 137\u2013156. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-22363-6_8"},{"key":"4_CR11","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.ejor.2005.06.044","volume":"176","author":"A Imai","year":"2007","unstructured":"Imai, A., Nishimura, E., Current, J.: A Lagrangian relaxation-based heuristic for the vehicle routing with full container load. Eur. J. Oper. Res. 176, 87\u2013105 (2007). https:\/\/doi.org\/10.1016\/j.ejor.2005.06.044","journal-title":"Eur. J. Oper. Res."},{"key":"4_CR12","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1016\/j.cie.2010.05.012","volume":"59","author":"C-H Chen","year":"2010","unstructured":"Chen, C.-H., Yan, S., Chen, M.: Applying Lagrangian relaxation-based algorithms for airline coordinated flight scheduling problems. Comput. Ind. Eng. 59, 398\u2013410 (2010). https:\/\/doi.org\/10.1016\/j.cie.2010.05.012","journal-title":"Comput. Ind. Eng."},{"key":"4_CR13","doi-asserted-by":"publisher","first-page":"61992","DOI":"10.1109\/ACCESS.2022.3181815","volume":"10","author":"Y Wang","year":"2022","unstructured":"Wang, Y., Song, R., He, S., Song, Z., Chi, J.: Optimizing train routing problem in a multistation high-speed railway hub by a Lagrangian relaxation approach. IEEE Access 10, 61992\u201362010 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3181815","journal-title":"IEEE Access"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-4755-3_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T23:17:33Z","timestamp":1690931853000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-4755-3_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819947546","9789819947553"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-4755-3_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"30 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhengzhou","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2023\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}