Cloud-based Cyber-Physical Robotic Mobile Fulfillment Systems Considering Order Correlation Pattern
| Autor: | K. L. Keung, Carman K. M. Lee, Ping Ji, Jiage Huo |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Apriori algorithm business.industry Computer science Distributed computing Supply chain Cyber-physical system Cloud computing 02 engineering and technology Grid Capacity management 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing business Cluster analysis |
| Zdroj: | IEEM |
| DOI: | 10.1109/ieem45057.2020.9309904 |
| Popis: | Ordering picking is the most time- and cost-consuming operation in the Robotic Mobile Fulfillment System (RMFS) and affects the entire supply chain operation efficiency and effectiveness. With the aid of digital operations, Cyber-Physical Systems (CPS) provide a nearly real-time control and response in the virtualized environment, thereby conducting a virtual prototype for near real-time simulation and prediction. The research presented in this paper explores the application of CPS in RMFS, considering the order correlation pattern. Four algorithms: Apriori algorithm, Frequent Pattern Growth algorithm, ECLAT algorithm and k-modes algorithm are introduced to reduce robotic conflicts of robots and enhance the capacity management in RMFS. The total completion time based on frequent itemset assignment is less than that based on random storage assignment. However, the dock grid conflicts are increased because the most frequent items are concentrated in a particular area. |
| Databáze: | OpenAIRE |
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