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| Lập kế hoạch tuyến đường tồn kho× | Hiệu ứng roi da× | |
|---|---|---|
| Lĩnh vực | Quản trị vận hành | Quản trị vận hành |
| Họ | Machine learning | Machine learning |
| Năm ra đời≠ | 2014 | 1961 |
| Người khởi xướng≠ | Coelho, L. C., Cordeau, J. F., & Laporte, G. | Jay Forrester |
| Loại≠ | Optimization problem | Phenomenon and analysis framework |
| Công trình gốc≠ | Coelho, L. C., Cordeau, J. F., & Laporte, G. (2014). Thirty years of inventory routing. Transportation Research Part B: Methodological, 55, 28-67. DOI ↗ | Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102. link ↗ |
| Tên gọi khác | IRP, vendor-managed logistics | demand amplification, Forrester effect |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | The Inventory Routing Problem (IRP) is an optimization problem that jointly determines inventory levels at customer locations, delivery routes, and shipment quantities to minimize total logistics and inventory holding costs. Rather than treating inventory management and vehicle routing as separate decisions, IRP recognizes that they are interdependent: larger shipments reduce routing costs but increase inventory holding costs, and vice versa. IRP is solved using mixed-integer programming, heuristics, and metaheuristics, and is a cornerstone of vendor-managed inventory (VMI) programs. | The Bullwhip Effect is a phenomenon in supply chain management where small fluctuations in end-customer demand cause progressively larger fluctuations in orders as one moves upstream from retail to distributors to manufacturers to suppliers. First formally documented by Jay Forrester in his 1961 system dynamics work, and later popularized by Lee, Padmanabhan, and Whang in 1997, the effect reveals how information delays and ordering strategies amplify demand variability throughout supply chains, leading to excess inventory, inefficient production scheduling, and increased costs. |
| ScholarGateBộ dữ liệu ↗ |
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