Dynamic items delivery network: prediction and clustering

Items delivery companies generally use a model to minimize delivery costs. From a mathematical perspective, the model is an objective function that involves constraints. Meanwhile, from a practical point of view, these constraints include aspects that affect item delivery, for example, delivery zone...

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Main Authors: Mokhammad R. Yudhanegara, Sapto W. Indratno, RR.Kurnia N. Sari
Format: Article
Language:English
Published: Elsevier 2021-05-01
Series:Heliyon
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844021010379
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spelling doaj-48dd4e795e31437bb84ae89231f999472021-06-03T14:44:59ZengElsevierHeliyon2405-84402021-05-0175e06934Dynamic items delivery network: prediction and clusteringMokhammad R. Yudhanegara0Sapto W. Indratno1RR.Kurnia N. Sari2Statistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, IndonesiaCorresponding author.; Statistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, IndonesiaStatistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, IndonesiaItems delivery companies generally use a model to minimize delivery costs. From a mathematical perspective, the model is an objective function that involves constraints. Meanwhile, from a practical point of view, these constraints include aspects that affect item delivery, for example, delivery zones, number of delivery vehicles, vehicle capacity, trip routes, etc. However, the models built so far have not paid attention to changes in road density. This aspect can result in a nonoptimal delivery model, which results in not a minimum delivery cost. For this reason, this paper discusses how to divide zones using the clustering method and predict changes in the shipping zone of a dynamic network using predictive distribution. So, the model can work optimally if the delivery zones and delivery strategies are suitable.http://www.sciencedirect.com/science/article/pii/S2405844021010379MathematicsSpectralDynamic networkPredictive distribution
collection DOAJ
language English
format Article
sources DOAJ
author Mokhammad R. Yudhanegara
Sapto W. Indratno
RR.Kurnia N. Sari
spellingShingle Mokhammad R. Yudhanegara
Sapto W. Indratno
RR.Kurnia N. Sari
Dynamic items delivery network: prediction and clustering
Heliyon
Mathematics
Spectral
Dynamic network
Predictive distribution
author_facet Mokhammad R. Yudhanegara
Sapto W. Indratno
RR.Kurnia N. Sari
author_sort Mokhammad R. Yudhanegara
title Dynamic items delivery network: prediction and clustering
title_short Dynamic items delivery network: prediction and clustering
title_full Dynamic items delivery network: prediction and clustering
title_fullStr Dynamic items delivery network: prediction and clustering
title_full_unstemmed Dynamic items delivery network: prediction and clustering
title_sort dynamic items delivery network: prediction and clustering
publisher Elsevier
series Heliyon
issn 2405-8440
publishDate 2021-05-01
description Items delivery companies generally use a model to minimize delivery costs. From a mathematical perspective, the model is an objective function that involves constraints. Meanwhile, from a practical point of view, these constraints include aspects that affect item delivery, for example, delivery zones, number of delivery vehicles, vehicle capacity, trip routes, etc. However, the models built so far have not paid attention to changes in road density. This aspect can result in a nonoptimal delivery model, which results in not a minimum delivery cost. For this reason, this paper discusses how to divide zones using the clustering method and predict changes in the shipping zone of a dynamic network using predictive distribution. So, the model can work optimally if the delivery zones and delivery strategies are suitable.
topic Mathematics
Spectral
Dynamic network
Predictive distribution
url http://www.sciencedirect.com/science/article/pii/S2405844021010379
work_keys_str_mv AT mokhammadryudhanegara dynamicitemsdeliverynetworkpredictionandclustering
AT saptowindratno dynamicitemsdeliverynetworkpredictionandclustering
AT rrkurniansari dynamicitemsdeliverynetworkpredictionandclustering
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