물품 출고 시간 최소화를 위한 강화학습 기반 적재창고 내 물품 재배치Minimize Order Picking Time through Relocation of Products in Warehouse based on Reinforcement Learning
- Other Titles
- Minimize Order Picking Time through Relocation of Products in Warehouse based on Reinforcement Learning
- Authors
- 이종환; 김여진; 김근태
- Issue Date
- Jun-2022
- Publisher
- 한국반도체디스플레이기술학회
- Keywords
- Reinforcement Learning; Q_learning; TD (Temporal Difference learning); Relocation; Machine Learning
- Citation
- 반도체디스플레이기술학회지, v.21, no.2, pp 90 - 94
- Pages
- 5
- Journal Title
- 반도체디스플레이기술학회지
- Volume
- 21
- Number
- 2
- Start Page
- 90
- End Page
- 94
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/26078
- ISSN
- 1738-2270
- Abstract
- In order to minimize the picking time when the products are released from the warehouse, they should be located close to the exit when the products are released. Currently, the warehouse determines the loading location based on the order of the requirement of products, that is, the frequency of arrival and departure. Items with lower requirement ranks are loaded away from the exit, and items with higher requirement ranks are loaded closer from the exit. This is a case in which the delivery time is faster than the products located near the exit, even if the products are loaded far from the exit due to the low requirement ranking. In this case, there is a problem in that the transit time increases when the product is released. In order to solve the problem, we use the idle time of the stocker in the warehouse to rearrange the products according to the order of delivery time. Temporal difference learning method using Q_learning control, which is one of reinforcement learning types, was used when relocating items. The results of rearranging the products using the reinforcement learning method were compared and analyzed with the results of the existing method.
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