Сравнение методов

	Маршрутизация запасов	Агрегатное планирование
Область	Операционный менеджмент	Операционный менеджмент
Семейство	Machine learning	Machine learning
Год появления	2014	1992
Автор метода	Coelho, L. C., Cordeau, J. F., & Laporte, G.	Wallace, T. F.
Тип	Optimization problem	Demand-supply planning framework
Основополагающий источник	Coelho, L. C., Cordeau, J. F., & Laporte, G. (2014). Thirty years of inventory routing. Transportation Research Part B: Methodological, 55, 28-67.	Wallace, T. F. (1992). Sales & Operations Planning: The how-to handbook. Cincinnati: APICS Publications.
Другие названия	IRP, vendor-managed logistics	sales and operations planning, production planning
Связанные	5	5
Сводка	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.