Optimising forecasting models for inventory planning

Machine Learning Models for Housing Prices Forecasting using Registration Data

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

Planning Horizon for Production Inventory Models with Production Rate Dependent on Demand and Inventory Level

This paper discusses why the selection of a finite planning horizon is preferable to an infinite one for a replenishment policy of production inventory models. In a production inventory model, the production rate is dependent on both the demand rate and the inventory level. When there is an exponentially decreasing demand, the application of an infinite planning horizon model is not suitable. T...

Forecasting the forecastability quotient for inventory management

This research develops and empirically tests a model for estimating the economic advantage of using a time phased order point system (TPOP) with time series forecasting rather than a simple reorder point system in an independent demand inventorymanagement context. We define the forecastability quotient (Q ) to support this economic analysis. We implement TPOP in our empirical analysis via doubl...

Forecasting for Inventory Control with Exponential Smoothing

Inventory Theory.S1 Inventory Models

9/9/01 Inventory Theory Inventory Theory.S1 Inventory Models This chapter will consider several model types. Supplement 2 describes deterministic models. Even though many features of an inventory system involve uncertainty of some kind, it is common to assume much simpler deterministic models for which solutions are found using calculus. Deterministic models also provide a base on which to inco...