Automating Capacity Pre-Booking at Warehouse Nodes of the Physical Internet

dc.contributor.author Zavitsas, Kostas
dc.contributor.author Kouloumbis, Makis
dc.contributor.author Sen, Juan Manuel
dc.contributor.corporatename VLTN
dc.contributor.corporatename INLECOM
dc.contributor.corporatename DHL
dc.date.accessioned 2023-07-21T11:36:58Z
dc.date.available 2023-07-21T11:36:58Z
dc.date.issued 2023-06
dc.description Presented at the 9th International Physical Internet Conference (IPIC 2023) 13-15 June 2023, Athens, Greece
dc.description.abstract The Physical Internet envisages the automation of the capacity booking process through the introduction of smart contracts. This requires the use of predictive models to determine what is a reasonable quantity to book, which are not well integrated into the decision making process. Currently, most warehouse operators book capacity only one day ahead when more concrete bookings’ data are available. The Paper proposes the integration of a pre-booking decision support tool to enhance the implementation of the predictive model outputs into smart contracts. Each delivery route is assumed to have a pricing structure that spans from ten days ahead to the day of delivery and contains early booking and cancellation fees. The aim of the tool is, considering the prediction quantity and pricing structure to determine an optimal strategy for issuing smart contract orders.
dc.identifier.uri https://hdl.handle.net/1853/72339
dc.identifier.uri https://doi.org/10.35090/gatech/7996
dc.publisher Georgia Institute of Technology
dc.subject Predictive modelling
dc.subject Inventory replenishment theory
dc.subject Warehouse PI node
dc.title Automating Capacity Pre-Booking at Warehouse Nodes of the Physical Internet
dc.type Text
dc.type.genre Poster
dspace.entity.type Publication
local.contributor.corporatename Physical Internet Center
local.relation.ispartofseries International Physical Internet Conference
relation.isOrgUnitOfPublication 98ebeaef-8476-422c-acfa-7b18aa9840a6
relation.isSeriesOfPublication 6b497421-893e-43c1-ab64-4582ed136698
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