A Comparative Analysis of Machine Learning Models for Time Prediction in Food Delivery Operations

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dc.contributor.authorYalçınkaya, Elmas
dc.contributor.authorHızıroğlu, Ourania Areta
dc.date.accessioned2025-03-21T07:38:23Z
dc.date.available2025-03-21T07:38:23Z
dc.date.issued2024
dc.departmentİzmir Bakırçay Üniversitesi
dc.description.abstractAccurate time estimation is crucial for ensuring customer satisfaction and operational efficiency in the growing food delivery sector. This paper focuses on comprehensively analyzing factors affecting food delivery times and assessing the effectiveness of machine learning models in forecasting delivery times. For this purpose, authors incorporated a detailed dataset from a food delivery company of the Kaggle platform, encompassing delivery address, order time, delivery time, weather conditions, traffic intensity, and delivery person's profile information. The study evaluated the effectiveness and performance of various machine learning models such as Linear Regression, Decision Trees, Random Forests, and particularly XGBRegressor, using metrics like MAE, RMSE, and R². The results demonstrate that ensemble methods— XGBRegressor—outperformed models in accurately predicting delivery times. Additionally, a thorough analysis of feature importance uncovered the factors influencing delivery time estimation. This study offers insights into leveraging machine learning techniques to optimize food delivery operations and enhance customer satisfaction. The discoveries can assist food delivery platforms in deploying effective time estimation models and emphasizing factors for predictions
dc.identifier.endpage56
dc.identifier.issn2757-9778
dc.identifier.issue1
dc.identifier.startpage43
dc.identifier.urihttps://hdl.handle.net/20.500.14034/2769
dc.identifier.urihttps://dergipark.org.tr/tr/pub/aita/issue/84471/1459560
dc.identifier.volume4
dc.language.isoen
dc.publisherİzmir Bakırçay Üniversitesi
dc.relation.ispartofArtificial Intelligence Theory and Applications
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20250319
dc.subjectMachine Learning
dc.subjectTime Estimation
dc.subjectFeature Importance
dc.subjectFood Delivery
dc.titleA Comparative Analysis of Machine Learning Models for Time Prediction in Food Delivery Operations
dc.typeArticle

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