Sammenlign metoder

	Økonomisk Ordrestørrelse (EOQ)	Stokastisk optimering
Fagområde	Operationsanalyse	Optimering
Familie	Regression model	Process / pipeline
Oprindelsesår	1913	1951 (SGD); 2014 (Adam)
Ophavsperson	Ford W. Harris	—
Type	Deterministic inventory optimization model	Gradient-based iterative optimization
Oprindelig kilde	Harris, F. W. (1913/1990). How many parts to make at once. Operations Research, 38(6), 947–950 (reprint).	Robbins, H. & Monro, S. (1951). A Stochastic Approximation Method. Annals of Mathematical Statistics, 22(3), 400-407.
Aliasser	Wilson EOQ Model, Harris-Wilson Model, Optimal Lot Size Model, Ekonomik Sipariş Miktarı	Stokastik Optimizasyon (SGD & Varyantları), stochastic gradient descent, SGD, Adam
Relaterede	3	3
Resumé	The Economic Order Quantity (EOQ) is a classic deterministic inventory model that identifies the order quantity minimizing the sum of annual ordering and holding costs. Introduced by Ford W. Harris in 1913 and later popularized by R. H. Wilson, EOQ assumes constant demand, fixed cost parameters, and instantaneous replenishment. It remains the foundational benchmark for inventory management in manufacturing, retail, and supply chain contexts where demand is relatively stable and costs are well-characterized.	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.