{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T12:44:01Z","timestamp":1666010641806},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,17]]},"abstract":"<jats:p>This note provides a solution to vehicle\u2019s compound allocation problem. It has been treated as a classification task employing different Machine Learning (ML) algorithms. It is performed using the known car attributes and the time that vehicles have spent in the compound region, i.e., inventory warehouse, waiting the customer delivery day. Classification results have been assessed with F1 Score and CatBoost has arisen as the best technique, with values larger than 70%. Finally, reallocation strategy has been tested and outcomes exhibit that company\u2019s expert performance is equaled or overcame with respect to time distribution.<\/jats:p>","DOI":"10.3233\/faia220329","type":"book-chapter","created":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T12:25:54Z","timestamp":1666009554000},"source":"Crossref","is-referenced-by-count":0,"title":["Binary Delivery Time Classification and Vehicle\u2019s Reallocation Based on Car Variants. SEAT: A Case Study"],"prefix":"10.3233","author":[{"given":"Juan Manuel","family":"Garc\u00eda S\u00e1nchez","sequence":"first","affiliation":[{"name":"Research Group of Data Science for the Digital Society (DS4DS), La Salle-Ramon Llull University"}]},{"given":"Xavier","family":"Vilas\u00eds Cardona","sequence":"additional","affiliation":[{"name":"Research Group of Data Science for the Digital Society (DS4DS), La Salle-Ramon Llull University"}]},{"given":"Alexandre","family":"Lerma Mart\u00edn","sequence":"additional","affiliation":[{"name":"SEAT S.A."}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Artificial Intelligence Research and Development"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220329","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T12:26:26Z","timestamp":1666009586000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220329"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,17]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220329","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,17]]}}}