RETAIL AND DOWNSTREAM SUPPLY CHAIN OPTIMIZATION THROUGH MASSIVELY PARALLEL PROCESSING OF DATA USING A DISTRIBUTED COMPUTING ENVIRONMENT

摘要

A method aggregates an advanced planning and forecasting raw data by multiple database management systems (DBMS) communicatively coupled to an extensible computation engine. Performing an advanced planning simulation a seasonality, a bundling structure, a reverse logistics chain, a logistical complexity, a replenishment demand of the retail goods, a downstream supply chain, an obsolesce risk of the retail goods and downstream supply chain by multiple processing nodes of the extensible computation engine. The method caches a result of the advanced planning simulation in an extensible memory cache communicatively coupled to the extensible computation engine and edge caching the same in an edge cache server near a geographical point of origin of the advanced planning and forecasting raw data. The extensible computing engine may employ a large number of processors to perform a set of coordinated computations in parallel through a distributed computing infrastructure for a specific advanced planning query.