Binary Delivery Time Classification and Vehicle's Reallocation Based on Car Variants. SEAT: A Case Study

Juan Manuel García Sánchez, Xavier Vilasís Cardona, Alexandre Lerma Martín

Producció científica: Capítol de llibreContribució a una conferènciaAvaluat per experts

Resum

This note provides a solution to vehicle's 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's expert performance is equaled or overcame with respect to time distribution.

Idioma originalAnglès
Títol de la publicacióArtificial Intelligence Research and Development - Proceedings of the 24th International Conference of the Catalan Association for Artificial Intelligence
EditorsAtia Cortes, Francisco Grimaldo, Tommaso Flaminio
EditorIOS Press BV
Pàgines147-150
Nombre de pàgines4
ISBN (electrònic)9781643683263
DOIs
Estat de la publicacióPublicada - 17 d’oct. 2022
Esdeveniment24th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2022 - Sitges, Spain
Durada: 19 d’oct. 202221 d’oct. 2022

Sèrie de publicacions

NomFrontiers in Artificial Intelligence and Applications
Volum356
ISSN (imprès)0922-6389

Conferència

Conferència24th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2022
País/TerritoriSpain
CiutatSitges
Període19/10/2221/10/22

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