The MIT Center for Transportation & Logistics (MIT CTL) and Mecalux have launched an artificial intelligence-based simulator aimed at optimising inventory distribution across warehouse networks, the center announced.
Called Genetic Evaluation & Simulation for Inventory Strategy (GENESIS), the platform was developed by MIT CTL’s Intelligent Logistics Systems Lab in collaboration with Mecalux, MIT CTL said in a statement.
It applies machine learning models and a genetic algorithm to analyse thousands of logistics scenarios, identifying optimal stock levels for each warehouse and timing for replenishment.
“The genetic algorithm enables multiple simulations to be run using different parameters until the most efficient logistics strategy is identified. Companies can compare scenarios and select the one that best fits their operations,” Matthias Winkenbach, Director of Research at MIT CTL, said in the MIT statement.
According to the release, GENESIS incorporates variables including forecasted regional demand, transportation costs, and warehouse capacity to test inventory strategies without affecting real-world operations. It generates recommended approaches alongside statistical dashboards that highlight consumption patterns, demand variability, stockout risks, and warehouse performance.
The center noted a key feature of the simulator is its ability to rebalance inventory across facilities. Rather than automatically placing new supplier orders, the system assesses whether excess stock in another warehouse can be reallocated more efficiently. It reported it provides guidance on transportation planning, including shipment consolidation and fulfillment location selection to reduce delivery times and costs.
“The real challenge wasn’t finding the right algorithm — it was making it fast enough to be practical. We developed GENESIS from the ground up to evaluate thousands of scenarios simultaneously rather than sequentially. What used to take days now takes minutes, which means companies can use it for real tactical planning, not just theoretical analysis,” Rodrigo Hermosilla, a research engineer at the MIT lab, said.
GENESIS is designed for both technical teams and business decision-makers. “The goal is to help companies minimise the total cost of their logistics network while ensuring the highest service level,” Javier Carrillo, CEO of Mecalux, said in the MIT release.
MIT CTL said the simulator represents an initial outcome of its collaboration with Mecalux, which now plans to expand AI applications to other logistics processes, including internal replenishment, digital twins for automated storage systems, and slotting optimisation.
