Decision pipeline for forecasting and optimization in resource planning

Abstract

A method for managing order processing includes obtaining a set of time series datasets associated with the order processing for an order processing system, generating forecasting parameters of the time series datasets using gradient recurrent units (GRU) and a latent space embedding, performing a cosine similarity of the forecasting parameters to obtain probability distributions of forecasting models, performing a stochastic optimization on the forecasting parameters using a two-stage cost-reward analysis to obtain intermediate parameters, obtaining finalized forecasting parameters based on the intermediate parameters, and initiating an agent deployment on the order processing system based on the finalized forecasting parameters.