Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이영해 | - |
dc.date.accessioned | 2020-09-29T01:18:00Z | - |
dc.date.available | 2020-09-29T01:18:00Z | - |
dc.date.issued | 2004-11 | - |
dc.identifier.citation | 2004년 대한산업공학회 추계학술대회 논문집, Page.65-71 | en_US |
dc.identifier.uri | http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE01963134&language=ko_KR | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/154327 | - |
dc.description.abstract | In 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.iso | ko_KR | en_US |
dc.publisher | 대한산업공학회 | en_US |
dc.title | 신경망을 이용한 공급사슬에서 주문충족을 위한 효율적 제품할당 정책 | en_US |
dc.title.alternative | An Effecient Allocation Policy for Order Fulfillment in the Supply Chain Using Neural Network | en_US |
dc.type | Article | en_US |
dc.contributor.googleauthor | 음승철 | - |
dc.contributor.googleauthor | 이영해 | - |
dc.contributor.googleauthor | 정정우 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | DEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING | - |
dc.identifier.pid | yhlee | - |
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