The Massachusetts Institute of Technology Center for Transportation & Logistics (MIT CTL) has initiated a new research lab, supported by Mecalux, to explore the potential of AI and machine learning in the logistics sector.
The Intelligent Logistics Systems Lab at MIT CTL aims to address significant logistics challenges by applying data-driven technologies. Mecalux, an intralogistics group, provided seed funding for this initiative. The lab will focus on how machine learning (ML) and artificial intelligence (AI) can enhance logistics operations and goods transport.
This collaboration between MIT CTL and Mecalux combines academic expertise from MIT with Mecalux’s practical experience in the industry. Mecalux plans to contribute technical insights and support from its software and automation specialists in the coming years.
The lab will investigate various research areas, aiming to develop state-of-the-art methods for some of the industry’s most complex issues. One focus will be on methods that offer highly accurate near-term predictions, crucial for services like same-day or sub-same-day delivery, addressing the growing demands of both consumers and commercial customers.
Dr. Matthias Winkenbach, Director of Research at MIT CTL, will lead the lab. “We aim to apply new AI- and machine-learning-based technologies to tackle the most impactful real-world challenges faced by companies and society,” said Winkenbach.
Technology for Operational Excellence
The new lab, supported by Mecalux, seeks to help the logistics industry design systems that offer excellent customer service, sustainability, and cost-effectiveness. Javier Carrillo, CEO of Mecalux, stated, “Operational excellence relies on the seamless integration of autonomous technology into warehouse processes. AI and machine learning are crucial in planning and monitoring these resources.”
The lab will also study the role of new technologies in controlling autonomous transport and delivery systems, and in automating processes like picking, sorting, packing, and shipping orders from warehouses or stores.
Another research focus will be developing hybrid methods at the intersection of operations research (OR) and ML. This aims to solve complex combinatorial optimization problems vital for logistics, including vehicle routing, inventory planning, network design, and transport planning.
About the MIT Center for Transportation & Logistics (CTL)
Founded in 1973, the MIT Center for Transportation & Logistics is a hub where industry leaders, professors, and students collaborate to advance supply chain education and research. MIT CTL’s team of over 80 researchers and faculty members from various disciplines work to deliver solutions that help organizations and societies thrive.
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