In a recent SupplyChainBrain podcast, MIT Senior Research Scientist Matthias Winkenbach discussed how GENESIS, developed in collaboration with Mecalux, helps companies evaluate thousands of inventory strategies in minutes.
“Many businesses no longer operate out of two or three big stockholding facilities but may actually have a global network of potentially dozens of warehouses,” said Winkenbach, Director of Research at MIT’s Center for Transportation & Logistics (CTL). “That makes it hard for companies to figure out where to store what.”
To address this challenge, MIT CTL and Mecalux collaborated on the development of GENESIS (Genetic Evaluation & Simulation for Inventory Strategy). This platform combines simulation and machine learning to assess inventory allocation strategies across warehouse networks.
GENESIS evaluates inventory and replenishment decisions from a network-wide perspective. The platform helps companies determine how much stock to store at each location, when to reorder products, and how to distribute inventory to support future demand.
“The big benefit of GENESIS is its speed,” said Winkenbach during the SupplyChainBrain podcast. “You need the network perspective, but you also need a tool that gives you a recommendation not in a matter of several hours but ideally in just a few minutes.” The platform can model thousands of inventory and demand scenarios simultaneously, enabling planners to assess multiple options and better understand the trade-offs between cost, inventory levels, and customer service.
Rather than automating decisions, GENESIS currently acts as a decision-support tool, providing recommendations and helping planners evaluate a wider range of potential future scenarios.