So sánh phương pháp

	Mô hình Tồn kho An toàn và Điểm Đặt lại Đơn hàng	Tối ưu hóa ngẫu nhiên
Lĩnh vực	Vận trù học	Tối ưu hóa
Họ	Regression model	Process / pipeline
Năm ra đời	1998	1951 (SGD); 2014 (Adam)
Người khởi xướng	Silver, Pyke & Peterson	—
Loại	Stochastic inventory control model	Gradient-based iterative optimization
Công trình gốc	Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory Management and Production Planning and Scheduling (3rd ed.). Wiley. ISBN: 978-0-471-11947-0	Robbins, H. & Monro, S. (1951). A Stochastic Approximation Method. Annals of Mathematical Statistics, 22(3), 400-407.
Tên gọi khác	Buffer Stock, Reserve Stock, Reorder-Point Model, Emniyet Stoğu	Stokastik Optimizasyon (SGD & Varyantları), stochastic gradient descent, SGD, Adam
Liên quan	3	3
Tóm tắt	Safety stock is an additional quantity of inventory held beyond expected demand during a replenishment lead time, designed to protect against stockouts caused by demand or supply uncertainty. Reorder-point models formalize this buffer by setting a trigger inventory level at which a new order is placed. Systematically developed within the stochastic inventory-control framework by Silver, Pyke, and Peterson (1998), the approach translates a desired customer-service level into a precise buffer quantity using the statistics of demand and lead-time variability.	Stochastic optimization is a family of iterative methods that minimize an objective function by computing gradients on randomly sampled subsets of data — mini-batches — rather than on the entire dataset at once. Pioneered by Robbins and Monro in 1951 as stochastic approximation, the approach became the standard engine for training large-scale machine-learning models through variants such as SGD with momentum, AdaGrad, RMSProp, and Adam.