Alternativer Text

Research

Methods

Our mission is to contribute to better and more sustainable solutions to the planning and execution of supply and value chain management. Better planning approaches are characterized by cost efficiency, robustness against uncertainty, volatility, and disruptions as well as the sustainable use of resources.

To achieve these targets, we investigate product and information flows and build decision support models and appropriate solution approaches to address such problems. Our research and its applications deal with conceptual structures of supply chain models (e.g., network design), fundamental aspects of operations management (e.g., inventory management), and transport logistics (e.g., vehicle routing). The objective is to build an understanding of how to manage and improve the sustainable performance of supply chains via better decision making and coordination. The growing amount of data that organizations collect, advances in computing power as well as progress in the development of analytical methods all provide new opportunities to improve supply chain management. It has become clear that new decision support systems, applications, and techniques are required to ensure efficient and accurate operations. This calls for new forms of interdisciplinary collaboration to exploit the full potential between disciplines such as Computer Science, Management and Engineering.

High-quality research requires collaboration with global experts. We therefore strive for international cooperation with well-known colleagues from international institutions. Much of the research work is carried out in cooperation with international partners from science and practice. Close interaction with the student courses will motivate students and enable them to get involved in various areas of research.

Cutting-edge, multi-disciplinary research is both qualitative and quantitative, usually involving strong analytical and modeling skills while also leveraging data analytics and empirical/statistical expertise. The spectrum in the arena of our core research primarily includes methods for discrete optimization and stochastic modeling. We also apply empirical research methods to foster exchange between industry and research. One example is exploratory studies carried out to identify and formulate new research questions in innovative areas. These studies analyze fundamental interrelationships and structures using expert surveys and qualitative content analysis. The findings allow new research questions and practice-relevant decision-making models to be formulated, which are then tested quantitatively or empirically.

Topics

Our aim is to drive the research agenda in Bioeconomy going forward as this is a unique opportunity for TUM Campus Straubing. We consider the combination of Bioeconomy with Value and Supply Chain Management in the areas of resource planning and the optimization of food supply chains as promising cooperation topics with the research group. Our research topics are structured around four areas, and will be described in the following:

1. Healthy and sustainable production and retailing of food and consumer goods

Supply with sustainable and healthy food represents an essential factor in health, wellbeing and lifestyle in industrialized countries. The German Bioeconomy Council recommends that research strategies should include “not only product innovations but also appropriate incentives and accompanying measures for sustainable and healthy eating habits.”

This requires dealing with logistics issues such as replenishment processes, order sizes, sourcing options, as well as questions of customer behavior such as the acceptance of sustainable products and substitutions. The following open-ended topics need to be understood:

  • Integrated assortment, store replenishment and inventory planning with varying consumer behavior patterns
  • Regionalization, segmentation and modularization of store and sourcing concepts
  • Evaluation of end-to-end effectiveness of retail supply chains, from agricultural production to shopping in store

2. Distribution and network planning with advanced warehousing and transport technologies

This research domain deals with technological advances in warehousing and transportation and their impact on network design and distribution options. The main goal is to consider environmental aspects by bundling transport flows. Current topics are:

  • Vehicle routing with multi-compartment trucks for multi-temperature logistics
  • Design of a warehouse network with fully automated picking.

3. Optimization of resource productivity and enabling biobased, circular value chains

Bioeconomy targets a more efficient use of biological resources by producing ideally more output with lower resource input required. This productivity gain is important across all industries, but particularly in sectors with limited availability of input resources. Current research topics in this area include:

  • Developing an optimization approach for service productivity from the perspectives of co-production, substitution of resources and stochastic customer demand
  • Developing a capacity planning approach for resource planning in maximum care hospitals

4. Sustainable operations management in the age of digitization

Our society is increasingly shaped by the expanding use of mobile and online technologies in daily life. The combination of information and communication technologies with Life Sciences offers opportunities to inform consumers about biotechnological advances and steer customers through the purchasing and consumption processes. Various research projects are being pursued:

  • Challenges to the design of supply chains in online food retailing
  • Inventory allocation of seasonal goods in omnichannel networks
  • The development of integrated sourcing and shipping concepts

Contact

Chair of Supply and Value Chain Management

Am Essigberg 3
94315 Straubing

Chair

Prof. Dr. rer. pol. Alexander Hübner

Team Assistants

Alexandra Lauber / Barbara Roth

Phone: +49 (0) 9421 187-246, -253
Mail: scm-info@cs.tum.de