Learning Outcomes

    The goal of this summer school is to forge a seed of young researchers from different disciplines, who share the interest in mechanisms for coordination logistics decisions of autonomous agents. Therefore, the course plan of the summer school Control Interfaces in Logistics: Data and Algorithms is designed to enable students to create more effective and efficient control interfaces in logistics. 
    After participating in the summer school, the student will be able to:
    • identify the research landscape on control interfaces,
    • explain and apply the core ideas of network flow optimization, big data analytics, control theory, and heuristics,
    • identify limitations and assumptions of distributed control,
    • clarify performance criteria for control interfaces and select evaluation criteria,
    • judge whether central or decentral coordination is appropriate,
    • verify and discuss whether one of these methods is an applicable solution approach for agiven scenario, and
    • analyze conflicting objectives and constraints with respect to the performance of a control interface.
    In the midterm, students will utilize this knowledge within their own projects to:
    • classify their research project in the topic landscape of the summer school,
    • sharpen the understanding of the working principles and realize the interdependencies between different levels and components of the systems,
    • improve communication and to increase understanding and exchange between the involved scientific disciplines.
    Finally, the summer school strives to generate a network of young researchers within the field of logistics. The aim of the network is to foster ideas from the various discipline and give rise to opportunities for joint research. To support this process, the summer school is accompanied by classical social elements such as get-together, dinner and guided tour, but also comprises new features such as research speed dating for scientific purpose and group lab sessions.