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Sequential graph-based routing algorithm for electrical harnesses, tubes, and hoses in a commercial vehicle

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dc.contributor.authorKim, Saekyeol-
dc.contributor.authorChoi, Taehyeok-
dc.contributor.authorKim, Shinyu-
dc.contributor.authorKwon, Taejoon-
dc.contributor.authorLee, Tae Hee-
dc.contributor.authorLee, Kwangrae-
dc.date.accessioned2021-07-30T04:50:10Z-
dc.date.available2021-07-30T04:50:10Z-
dc.date.created2021-05-11-
dc.date.issued2021-04-
dc.identifier.issn0956-5515-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/1484-
dc.description.abstractThe routing design of the various electrical wires, tubes, and hoses of a commercial vehicle requires a significant number of man-hours because of the variety of the commercial vehicles, frequent design changes of other vehicular components and the manual trial-and-error approaches. This study proposes a new graph-based routing algorithm to find the collision-free routing path in the constrained space of a commercial vehicle. Minimal spanning tree is adopted to connect multi-terminal points in a graph and Dijkstra's algorithm is used to find the shortest route among the candidate paths; the design domain is divided into several sub-domains to simplify the graph and the proposed algorithm solves the routing problems in a sequential manner to deal intermediate points. Then, the proposed method was applied to the design of the routes for four different routing components of a commercial truck. The results indicate that the developed methodology can provide a satisfactory routing design satisfying all the requirements of the design experts in the automotive industry.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-
dc.titleSequential graph-based routing algorithm for electrical harnesses, tubes, and hoses in a commercial vehicle-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Tae Hee-
dc.identifier.doi10.1007/s10845-020-01596-9-
dc.identifier.scopusid2-s2.0-85085519553-
dc.identifier.wosid000553970500002-
dc.identifier.bibliographicCitationJOURNAL OF INTELLIGENT MANUFACTURING, v.32, no.4, pp.917 - 933-
dc.relation.isPartOfJOURNAL OF INTELLIGENT MANUFACTURING-
dc.citation.titleJOURNAL OF INTELLIGENT MANUFACTURING-
dc.citation.volume32-
dc.citation.number4-
dc.citation.startPage917-
dc.citation.endPage933-
dc.type.rimsART-
dc.type.docTypeArticle; Early Access-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.subject.keywordPlusANT COLONY OPTIMIZATION-
dc.subject.keywordPlusGENETIC ALGORITHM-
dc.subject.keywordPlusPIPE-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusMODEL-
dc.subject.keywordPlusNETWORKS-
dc.subject.keywordPlusLAYOUT-
dc.subject.keywordAuthorCommercial vehicle-
dc.subject.keywordAuthorDijkstra&apos-
dc.subject.keywordAuthors algorithm-
dc.subject.keywordAuthorMinimal spanning tree-
dc.subject.keywordAuthorPipe routing algorithm-
dc.subject.keywordAuthorRouting design methodology-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s10845-020-01596-9-
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