{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T15:36:16Z","timestamp":1742916976077,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031568251"},{"type":"electronic","value":"9783031568268"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-56826-8_36","type":"book-chapter","created":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T05:01:44Z","timestamp":1712034104000},"page":"467-476","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Analysis of Machine Learning Approaches to Predict Disruptions in Truck Appointment Systems"],"prefix":"10.1007","author":[{"given":"Mauricio Randolfo Flores","family":"da Silva","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mirko","family":"K\u00fcck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enzo Morosini","family":"Frazzon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julia Cristina","family":"Bremen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,3]]},"reference":[{"issue":"4","key":"36_CR1","doi-asserted-by":"publisher","first-page":"83","DOI":"10.3390\/jmse7040083","volume":"7","author":"J Chen","year":"2019","unstructured":"Chen, J., Huang, T., et al.: Constructing governance framework of a green and smart port. J. Mar. Sci. Eng. 7(4), 83 (2019)","journal-title":"J. Mar. Sci. Eng."},{"issue":"9","key":"36_CR2","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1080\/15568318.2019.1610919","volume":"14","author":"A Molavi","year":"2020","unstructured":"Molavi, A., Lim, G.J., Race, B.: A framework for building a smart port and smart port index. Int. J. Sustain. Transp. 14(9), 686\u2013700 (2020)","journal-title":"Int. J. Sustain. Transp."},{"key":"36_CR3","doi-asserted-by":"crossref","unstructured":"Flores da Silva, M.R., Chaves, G.L.D., Frazzon, E.M.: Modelling container dynamics under the COVID-19 disruptive scenario. IFAC-PapersOnline 56(2), 10351\u201310356 (2023)","DOI":"10.1016\/j.ifacol.2023.10.1046"},{"issue":"April","key":"36_CR4","doi-asserted-by":"publisher","first-page":"107502","DOI":"10.1016\/j.ijpe.2019.09.023","volume":"22","author":"J Mar-Ortiz","year":"2020","unstructured":"Mar-Ortiz, J., Castillo-Garc\u00eda, N., Gracia, M.: A decision support system for a capacity management problem at a container terminal. Int. J. Prod. Econ. 22(April), 107502 (2020)","journal-title":"Int. J. Prod. Econ."},{"issue":"1","key":"36_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3141\/2548-01","volume":"2548","author":"N Huynh","year":"2016","unstructured":"Huynh, N., Smith, D., Harder, F.: Truck appointment systems: where we are and where to go from here. Transp. Res. Rec. 2548(1), 1\u20139 (2016)","journal-title":"Transp. Res. Rec."},{"key":"36_CR6","doi-asserted-by":"publisher","first-page":"83387","DOI":"10.1109\/ACCESS.2020.2990961","volume":"8","author":"KLA Yau","year":"2020","unstructured":"Yau, K.L.A., Peng, S., Qadir, J., Low, Y., Ling, M.: Towards smart port infrastructures: enhancing port activities using information and communications technology. IEEE Access 8, 83387\u201383404 (2020)","journal-title":"IEEE Access"},{"key":"36_CR7","doi-asserted-by":"publisher","unstructured":"da Silva, M.R.F., Agostino, I.R., Frazzon, E.M.: Integration of machine learning and simulation for dynamic rescheduling in truck appointment systems. Simul. Model. Pract. Theory 125(May 2023), 102747 (2023). https:\/\/doi.org\/10.1016\/j.simpat.2023.102747","DOI":"10.1016\/j.simpat.2023.102747"},{"issue":"4","key":"36_CR8","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1080\/03088839.2019.1693063","volume":"47","author":"N Li","year":"2020","unstructured":"Li, N., Chen, G., Ng, M., Talley, W., Jin, Z.: Optimized appointment scheduling for export container deliveries at marine terminals. Marit. Policy Manag. 47(4), 456\u2013478 (2020)","journal-title":"Marit. Policy Manag."},{"key":"36_CR9","doi-asserted-by":"publisher","first-page":"102281","DOI":"10.1016\/j.ijinfomgt.2020.102281","volume":"57","author":"E Frazzon","year":"2021","unstructured":"Frazzon, E., Freitag, M., Ivanov, D.: Intelligent methods and systems for decision-making support: toward digital supply chain twins. Int. J. Inf. Manag. 57, 102281 (2021)","journal-title":"Int. J. Inf. Manag."},{"issue":"10","key":"36_CR10","doi-asserted-by":"publisher","first-page":"3382","DOI":"10.1109\/TLA.2015.7387245","volume":"13","author":"NK Gimenez Isasi","year":"2015","unstructured":"Gimenez Isasi, N.K., Frazzon, E.M., Uriona, M.: Big data and business analytics in the supply chain: a review of the literature. IEEE Lat. Am. Trans. 13(10), 3382\u20133391 (2015)","journal-title":"IEEE Lat. Am. Trans."},{"issue":"3","key":"36_CR11","first-page":"443","volume":"31","author":"H Adonor","year":"2021","unstructured":"Adonor, H.: Supply chain resilience: an adaptive cycle approach. Int. J. Logist. Manag. 31(3), 443\u2013463 (2021)","journal-title":"Int. J. Logist. Manag."},{"key":"36_CR12","doi-asserted-by":"crossref","unstructured":"Flores da Silva, M., Frazzon, E.M., Silva, V.: Design of flexible truck appointment system based on machine learning approach. Int. J. Logist. Syst. Manag. (2022)","DOI":"10.1504\/IJLSM.2021.10043983"},{"issue":"5","key":"36_CR13","doi-asserted-by":"publisher","first-page":"9962","DOI":"10.3390\/s150509962","volume":"15","author":"R Guinness","year":"2015","unstructured":"Guinness, R.: Beyond where to how: a machine learning approach for sensing mobility contexts using smartphone sensors. Sensors (Switzerland) 15(5), 9962\u20139985 (2015)","journal-title":"Sensors (Switzerland)"},{"key":"36_CR14","first-page":"193","volume":"37","author":"S Kim","year":"2020","unstructured":"Kim, S., Vu, Q., Papazafeiropoulos, G., Kong, Z., Truong, V.: Comparison of machine learning algorithms for regression and classification of ultimate load-carrying capacity of steel frames. Steel Compos. Struct. Int. J. 37, 193\u2013209 (2020)","journal-title":"Steel Compos. Struct. Int. J."},{"key":"36_CR15","unstructured":"Burkov, A.: The Hundred-Page Machine Learning Book, 1st edn. Andriy Burjov, Canada (2019)"},{"key":"36_CR16","doi-asserted-by":"crossref","unstructured":"Hastie, T. Tibshirani, R. Friedman, J.H. Friedman, J.H.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2 edn. Springer, New York (2009).","DOI":"10.1007\/978-0-387-84858-7"},{"key":"36_CR17","unstructured":"Chinnamgari, S.: R Machine Learning Projects: Implemented Supervised, Unsupervised, and Reinforcement Learning Techniques Using R 3.5. Packt Publishing Ltd., Birmingham (2019)"},{"key":"36_CR18","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1007\/s12599-020-00653-0","volume":"62","author":"A Balster","year":"2020","unstructured":"Balster, A., Hansen, O., Friedrich, H., Ludwig, A.: An ETA prediction model for intermodal transport networks based on machine learning. Bus. Inf. Syst. Eng. 62, 403\u2013416 (2020)","journal-title":"Bus. Inf. Syst. Eng."},{"issue":"1","key":"36_CR19","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1017\/S0373463320000363","volume":"74","author":"R Fiskin","year":"2020","unstructured":"Fiskin, R., Cakir, E., Sevgili, C.: Decision tree and logistic regression analysis to explore factors contributing to harbour tugboat accidents. J. Navig. 74(1), 79\u2013104 (2020)","journal-title":"J. Navig."},{"key":"36_CR20","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.eswa.2018.02.022","volume":"102","author":"S Srinivas","year":"2018","unstructured":"Srinivas, S., Ravindran, A.: Optimizing outpatient appointment system using machine learning algorithms and scheduling rules: a prescriptive analytics framework. Expert Syst. Appl. 102, 245\u2013261 (2018)","journal-title":"Expert Syst. Appl."},{"key":"36_CR21","doi-asserted-by":"publisher","first-page":"101840","DOI":"10.1016\/j.jairtraman.2020.101840","volume":"88","author":"Z Wang","year":"2020","unstructured":"Wang, Z., Liang, M., Delahaye, D.: Automated data-driven prediction on aircraft estimated time of arrival. J. Air Transp. Manag. 88, 101840 (2020)","journal-title":"J. Air Transp. Manag."},{"issue":"April","key":"36_CR22","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1016\/j.cie.2019.04.044","volume":"132","author":"Y Kang","year":"2019","unstructured":"Kang, Y., Lee, S., Chung, B.: Learning-based logistics planning and scheduling for crowdsourced parcel delivery. Comput. Ind. Eng. 132(April), 271\u2013279 (2019)","journal-title":"Comput. Ind. Eng."},{"issue":"3","key":"36_CR23","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1214\/16-STS602","volume":"32","author":"D Bertsimas","year":"2017","unstructured":"Bertsimas, D., King, A.: Logistic regression: from art to science. Stat. Sci. 32(3), 367\u2013384 (2017)","journal-title":"Stat. Sci."},{"issue":"21","key":"36_CR24","first-page":"3018","volume":"97","author":"HM Putra","year":"2019","unstructured":"Putra, H.M., Nasrudin, M.F.: Model for estimating bus arrival times by comparing various classifications. J. Theor. Appl. Inf. Technol. 97(21), 3018\u20133030 (2019)","journal-title":"J. Theor. Appl. Inf. Technol."},{"key":"36_CR25","unstructured":"Hyndman, R.J., Athanasopoulos, G.: Forecasting: Principles and Practice, 3rd edn. OText, Melbourne, Australia (2021)"}],"container-title":["Lecture Notes in Logistics","Dynamics in Logistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-56826-8_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T05:06:53Z","timestamp":1712034413000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-56826-8_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031568251","9783031568268"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-56826-8_36","relation":{},"ISSN":["2194-8917","2194-8925"],"issn-type":[{"type":"print","value":"2194-8917"},{"type":"electronic","value":"2194-8925"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"LDIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Dynamics in Logistics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bremen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 February 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 February 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ldic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.uni-bremen.de\/ldic-conference\/about-ldic","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}