DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Jang, Young Jae | - |
dc.contributor.advisor | 장영재 | - |
dc.contributor.author | Sim, Hyeonjun | - |
dc.date.accessioned | 2019-09-03T02:42:30Z | - |
dc.date.available | 2019-09-03T02:42:30Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=733841&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/266266 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 산업및시스템공학과, 2018.2,[iii, 32 p. :] | - |
dc.description.abstract | In the fashion industry, brands have updated the sales season frequently with more varied but smaller production quantities. Due to a limited amount of production, some products are not always supplied to all stores. Therefore, company managers have to make decisions to distribute the products. To satisfy a wide range of customer needs, a visual variety should be considered in the initial distribution. We turned product images into numbers using a convolutional autoencoder. The numeric values were utilized to measure the visual variety. The proposed distribution optimization model maximized the variety of products stores receive while considering operational constraints. We applied the model to a base to verify the applicability of the proposed model. The distribution results were consistent with what the company is pursuing. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Supply chain management | - |
dc.subject | Fashion industry | - |
dc.subject | Machine learning | - |
dc.subject | Visual variety | - |
dc.subject | Mathematical distribution optimization | - |
dc.subject | 물류 공급망 관리▼a패션 산업▼a기계 학습▼a시각적 다양성▼a수학적 배분 최적화 | - |
dc.title | Inventory distribution considering Image-based fashion product variety | - |
dc.title.alternative | 이미지 기반의 패션 상품 다양성을 고려한 재고 배분 연구 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :산업및시스템공학과, | - |
dc.contributor.alternativeauthor | 심현준 | - |
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