The Intelligent Logistics Systems Lab brings together researchers from MIT’s Center for Transportation & Logistics and industry experts from Mecalux to develop and implement AI-based solutions targeting some of the most pressing and high-impact challenges in logistics.
The lab, founded with support from Mecalux, aims to drive advancements that enhance efficiency, sustainability, resilience, and customer satisfaction within the logistics industry.
News
September 25, 2026
The MIT Center for Transportation & Logistics (MIT CTL) and Mecalux have launched an executive course. The program will give senior executives practical insights into applying AI to warehousing and supply chain decision-making.
Interviews
August 24, 2026
Videos
August 21, 2026
Mecalux and MIT CTL break down autonomous intelligence and what it means for the logistics world — all in just 90 seconds. Autonomous intelligence automates routine tasks, optimizes processes, and analyzes patterns to generate actionable insights.
Videos
August 7, 2026
Mecalux and MIT CTL break down predictive intelligence and explain how it’s transforming logistics — all in just 90 seconds. By forecasting future events with greater accuracy, businesses can improve planning, reduce risk, and make more proactive decisions.
News
June 29, 2026
In the SupplyChainBrain podcast, MIT Senior Research Scientist Matthias Winkenbach explains how GENESIS, developed with Mecalux, optimizes inventory strategy. The platform helps allocate inventory efficiently across multiple warehouses while serving as a decision-support tool.
Videos
June 5, 2026
Mecalux and MIT CTL break down augmented intelligence and what it means for the logistics world, all in just 90 seconds. Companies and professionals across all industries — including logistics — can benefit from having more information at their fingertips.
News
June 1, 2026
Mecalux and MIT presented their latest developments in warehouse AI at a Gartner conference on AI-driven logistics. The organizations unveiled GENESIS, a simulator capable of evaluating thousands of logistics scenarios in minutes using advanced AI.
Videos
May 22, 2026
Users will be able to define parameters such as the number of shuttles and the warehouse layout to test different 3D Automated Pallet Shuttle configurations and identify the one that delivers the highest throughput.
Videos
April 20, 2026
The Massachusetts Institute of Technology and Mecalux are developing an AI system to optimize warehouse replenishment. The solution analyzes demand, inventory, and resources to determine when and where to restock, reducing shortages and improving order picking efficiency.
With the support of Mecalux, we are confident that our research will lead to groundbreaking advancements in the field.
Our partnership with MIT CTL will drive research-based innovation into practice and set new standards for operational excellence in the industry.
The objective of our collaboration with Mecalux is to foster disruptive innovation and achieve highly impactful use cases where AI transforms industry decision-making.
High-impact predictive capabilities powered by AI and ML, including the development of highly accurate near-term forecasting essential for highly responsive logistics services such as same-day and sub-same-day delivery.
New methods and models that combine operations research with ML and AI to solve complex combinatorial optimization problems critical for logistics, such as vehicle routing, inventory planning, and network design in a richer context of non-trivial real-world objectives, constraints, and uncertainties.
Control and impact of advanced logistics systems and technologies that can independently perform tasks, make decisions, and learn from their environments without continuous human intervention. For instance, this includes mobile robots that assist or replace humans in warehousing or delivery activities and that operate autonomously in complex and dynamic settings.
Collective behavior and coordination of autonomous systems or entities working together to solve a common problem. In the context of intelligent logistics systems, this involves the synchronization and cooperation of multiple agents such as autonomous robots or crowd-sourced carriers to optimize system performance.
How human decision-making can be enhanced by combining human intelligence with AI. Specifically, the lab intends to explore how decision support systems and operations management software can effectively combine human expertise with AI-driven insights.
