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dc.contributor.author이영해-
dc.date.accessioned2020-09-29T01:18:00Z-
dc.date.available2020-09-29T01:18:00Z-
dc.date.issued2004-11-
dc.identifier.citation2004년 대한산업공학회 추계학술대회 논문집, Page.65-71en_US
dc.identifier.urihttp://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE01963134&language=ko_KR-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/154327-
dc.description.abstractIn the current global business environment, it is very important how to allocate products from the manufacturer to distributors for the efficient response to customer orders. Imaginary demands ordered by distributors are the big obstacle to the efficient allocation of products. If the manufacturer can become aware of imaginary demands included in distributors' orders, it is possible to realize the high level order fulfillment through the efficient allocation of products using neural network. We propose new allocation policy considering imaginary demands. In this study, the backpropagation algorithm, one of algorithms in neural network, is used to find imaginary demands from the distributors' orders.en_US
dc.language.isoko_KRen_US
dc.publisher대한산업공학회en_US
dc.title신경망을 이용한 공급사슬에서 주문충족을 위한 효율적 제품할당 정책en_US
dc.title.alternativeAn Effecient Allocation Policy for Order Fulfillment in the Supply Chain Using Neural Networken_US
dc.typeArticleen_US
dc.contributor.googleauthor음승철-
dc.contributor.googleauthor이영해-
dc.contributor.googleauthor정정우-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF ENGINEERING SCIENCES[E]-
dc.sector.departmentDEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING-
dc.identifier.pidyhlee-
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > INDUSTRIAL AND MANAGEMENT ENGINEERING(산업경영공학과) > Articles
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