Finding the Best Location for Logistics Hub Based on Actual Parcel Delivery Data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, Hayoon | - |
dc.contributor.author | H.Y. | - |
dc.contributor.author | Han, Insoo | - |
dc.contributor.author | I. | - |
dc.date.available | 2021-03-17T07:59:47Z | - |
dc.date.created | 2021-02-26 | - |
dc.date.issued | 2019 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/12736 | - |
dc.description.abstract | So many national and international packets are traveling around in this time. The parcel delivery service is a major part of nationwide logistics. It is reported that wrong routes for logistic causes economical disadvantage both in time and in cost. It is possible to collect actual delivery data from logistics company or Internet of Things devices. Based on actual route of packet delivery, we collected 100,000 delivery data over Republic of Korea and analyzed for optimal hub candidate locations in terms of minimum distance and minimum time. From the raw delivery data set, actual delivery paths were calculated in terms of big data analytics Using Longest Common Route Subsequence algorithm, the most common paths can be identified. From the economic aspect, regarding minimum distance and time, optimal hub location candidates were voted and identified. With several hub locations, optimal distance and time can be calculated from the location of optimal hub candidates. | - |
dc.publisher | SPRINGER INTERNATIONAL PUBLISHING AG | - |
dc.title | Finding the Best Location for Logistics Hub Based on Actual Parcel Delivery Data | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Song, Hayoon | - |
dc.identifier.doi | 10.1007/978-3-030-24289-3_45 | - |
dc.identifier.scopusid | 2-s2.0-85069230106 | - |
dc.identifier.wosid | 000661318700045 | - |
dc.identifier.bibliographicCitation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.11619 LNCS, pp.603 - 615 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.volume | 11619 LNCS | - |
dc.citation.startPage | 603 | - |
dc.citation.endPage | 615 | - |
dc.type.rims | ART | - |
dc.type.docType | Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.subject.keywordAuthor | Parcel service | - |
dc.subject.keywordAuthor | Optimum logistics hub location | - |
dc.subject.keywordAuthor | Longest Common Route Subsequence algorithm | - |
dc.subject.keywordAuthor | Big data analytics | - |
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