For decades, researchers have grappled with the challenge of adapting the Economic Production Quantity (EPQ) model to multi-item production settings, characterized by the shared use of a single resource with limited capacity for manufacturing various items. Moreover, today’s production systems are marked by an increasing demand for product variety and ever more stringent customization requirements.

Traditionally, researchers have addressed this issue through economic lot scheduling, keeping the interest of the scientific community alive. Despite the significance of these approaches, there remain limitations in adapting the EPQ model to multi-product ‘pull’ production systems, including the practical difficulties of implementing scheduling.

The current work, “Economic production quantity (EPQ) model in “pull” managed single-machine multi-item production systems”, published on Annals of operations research, conducted by Professors Rossella Pozzi and Tommaso Rossi from LIUC and Salani from the Dalle Molle Institute for Artificial Intelligence (IDSIA) aims to overcome these limitations by introducing a methodology that combines a previous mathematical model with considerations on the production frequency of items, necessary to define feasible solutions. The effectiveness and practicality of the proposed model have been evaluated by applying it to well-known benchmarking literature cases (Bomberger’s, Eilon’s, and Mallya’s problems) and a wide set of test problems.

This new methodology paves the way for significant improvements in multi-item production management, offering a more readily applicable approach in real production systems. Research in this area represents a step forward towards more efficient production systems capable of dynamically responding to the challenges of the current market.