Interdisciplinary Research Area

Planning & Logistics

The use of Artificial Intelligence in logistics can help to optimize complex processes and thus make them more resilient and resource-efficient. Logistics also gives rise to challenging questions for interdisciplinary research at the Lamarr Institute.

Looking at the status quo, logistics is currently still a business that is strongly driven by analog processes and manual work. Although logistical operations – getting X from A to B – are not complicated when viewed individually, the complexity of the problem quickly increases when a large number of goods need to be brought to a multitude of locations. Mathematically, such processes can be described by a super-exponentially growing solution space. The Travelling Salesman Problem is a well-known example of such a complex optimization problem.

PlanungUndLogistik quadratisch - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Logistical Optimization Ensures Greater Resilience and Preserves Resources

The fact that logistics plays a key role in our lives and is closely interlinked with critical infrastructure has not only been evident since crises such as the coronavirus pandemic or the war in Ukraine. A single ship blocking the Suez Canal disrupts sensitive supply chains, with consequences for the global economy.

The Lamarr Institute’s research into Machine Learning and Artificial Intelligence can help to continuously adapt and optimize processes in logistics and thus increase resilience not only in the event of logistical disruptions. Up to now, attempts have often only been made to minimize logistics costs. However, logistics optimization is multi-criteria. In future, the use of AI can ensure that solutions also become more resource-efficient and environmentally friendly.

Contact persons

Sören Kerner

Dr. Sören Kerner

Area Chair Planning & Logistics to the profile

Interdisciplinary Exchange on the Use of AI in Logistics

The interdisciplinary research field of logistics gives rise to many current and challenging questions for AI research. How can large language models be used to optimize documents for tenders, for example? Can generative AI help with warehouse planning and optimize intralogistics? How can findings from the interdisciplinary research area of embodied AI be used to develop robots for automation in logistics? Can Artificial Intelligence contribute to self-organization in logistics?

Logistics as the all-pervasive principle of the purposeful movement of things affects us all in our everyday lives and at work. The use of Artificial Intelligence in logistics can therefore help to make life step by step safer, more convenient and easier for each and every one of us.