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| 库存路径问题× | 综合计划× | |
|---|---|---|
| 领域 | 运营管理 | 运营管理 |
| 方法族 | Machine learning | Machine learning |
| 起源年份≠ | 2014 | 1992 |
| 提出者≠ | Coelho, L. C., Cordeau, J. F., & Laporte, G. | Wallace, T. F. |
| 类型≠ | Optimization problem | Demand-supply planning framework |
| 开创性文献≠ | Coelho, L. C., Cordeau, J. F., & Laporte, G. (2014). Thirty years of inventory routing. Transportation Research Part B: Methodological, 55, 28-67. DOI ↗ | Wallace, T. F. (1992). Sales & Operations Planning: The how-to handbook. Cincinnati: APICS Publications. link ↗ |
| 别名 | IRP, vendor-managed logistics | sales and operations planning, production planning |
| 相关 | 5 | 5 |
| 摘要≠ | 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. | Aggregate Planning (or Sales & Operations Planning, S&OP) is a collaborative, iterative process that balances demand and supply at a high level—typically grouping products into families and planning over a 3–18 month horizon. Developed formally by Tom Wallace and popularized through APICS, aggregate planning helps organizations align sales forecasts, production capacity, inventory, and workforce to meet demand efficiently while managing costs. It serves as the bridge between strategic business plans and detailed operational execution. |
| ScholarGate数据集 ↗ |
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