Optimization of ATM cash replenishment with group-demand forecasts

Basit Öğe Kaydı
dc.authoridDUMAN, EKREM/0000-0001-5176-6186
dc.authorwosidDUMAN, EKREM/GXN-3001-2022
dc.contributor.authorEkinci, Yeliz
dc.contributor.authorLu, Jye-Chyi
dc.contributor.authorDuman, Ekrem
dc.date.accessioned2024-07-18T20:42:36Z
dc.date.available2024-07-18T20:42:36Z
dc.date.issued2015
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractIn ATM cash replenishment banks want to use less resources (e.g., cash kept in ATMs, trucks for loading cash) for meeting fluctuated customer demands. Traditionally, forecasting procedures such as exponentially weighted moving average are applied to daily cash withdraws for individual ATMs. Then, the forecasted results are provided to optimization models for deciding the amount of cash and the trucking logistics schedules for replenishing cash to all ATMs. For some situations where individual ATM withdraws have so much variations (e.g., data collected from Istanbul ATMs) the traditional approaches do not work well. This article proposes grouping ATMs into nearby-location clusters and also optimizing the aggregates of daily cash withdraws (e.g., replenish every week instead of every day) in the forecasting process. Example studies show that this integrated forecasting and optimization procedure performs better for an objective in minimizing costs of replenishing cash, cash-interest charge and potential customer dissatisfaction. (C) 2014 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) scholarshipen_US
dc.description.sponsorshipThis research was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) scholarship awarded for a postdoctoral research position for Dr. Yeliz Ekinci. The authors are thankful to the anonymous financial services company that supplied the data and expert opinion. The interpretation and conclusions revealed in this study do not represent the official perspectives of the institutes stated above.en_US
dc.identifier.doi10.1016/j.eswa.2014.12.011
dc.identifier.endpage3490en_US
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.issue7en_US
dc.identifier.scopus2-s2.0-84920973939en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage3480en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2014.12.011
dc.identifier.urihttps://hdl.handle.net/11411/7357
dc.identifier.volume42en_US
dc.identifier.wosWOS:000350182600016en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAggregationen_US
dc.subjectInformation Based Optimizationen_US
dc.subjectModel Quality İmprovementen_US
dc.subjectLogistics Schedulingen_US
dc.subjectTime-Seriesen_US
dc.subjectAggregationen_US
dc.subjectModelen_US
dc.titleOptimization of ATM cash replenishment with group-demand forecastsen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

Web of Science Indexed Publications
Scopus Indexed Publications