Intelligent Systems in Logistics

In recent years, the complexity and dynamics in logistic processes have been increased due to shorter product life cycles, the rising number of product variants as well as the growing number of transnational links and dependencies within the production processes between companies.

The research group Intelligent Systems in Logistics develops approaches and methods for controlling, modeling, simulation and evaluation of logistic processes in order to optimize the planning and controlling processes of logistic service providers. The goal is to improve the service quality while ensuring cost- and time-efficiency as well as sustainable production and transport processes within the supply network of companies.

The research field covers planning and scheduling algorithms, (distributed) decision making, multiagent systems and interaction, distributed artificial intelligence, knowledge management, data mining, and simulation. New approaches, algorithms, and interaction mechanisms are evaluated with the PlaSMA Simulation Framework as well as directly with production robots in cooperation with the BIBA. The PlaSMA Framework enables the simulation of logistic scenarios on real-world infrastructures. It provides a discrete time simulation that ensures a correct conservative synchronization with time model adequacy, causality and reproducibility.

The research group is associated with the Research Cluster for Dynamics in Logistics and was part of the Collaborative Research Centre 637 Autonomous Cooperating Logistic Processes – A Paradigm Shift and its Limitations (CRC 637). Concepts and approaches developed within the CRC 637 have been adapted and refined to apply them successfully within current processes of our industrial partners to indentify new potentials for optimization. The research focuses on developing innovative approaches to enable autonomous logistic processes and to apply them in current industrial processes. Our objective is to improve planning and controlling processes with artificial intelligence in order to meet the increasing requirements and new challenges in logistics.

Several PHD students are associated with the International Graduate School of Logistics (IGS).