Lübben, R., & Fidler, M. (2016). A Benchmark for the Performance of Time-varying Closed-loop Flow Control with Application to TCP. CoRR, abs/1609.00653.
Garousi, V., Petersen, K., & Ozkan, B. (2016). Challenges and best practices in industry-academia collaborations in software engineering: A systematic literature review. Information and Software Technology, 79, 106–127.
Schlipf, D., Haizmann, F., Cosack, N., Siebers, T., & Cheng, P. W. (2015). Detection of wind evolution and lidar trajectory optimization for lidar-assisted wind turbine control. Meteorologische Zeitschrift, 24, 565–579. http://doi.org/10.1127/metz/2015/0634 (Original work published 2026)
Schlipf, D., Simley, E., Lemmer, F., Pao, L., & Cheng, P. W. (2015). Collective pitch feedforward control of floating wind turbines using Lidar. Journal of Ocean and Wind Energy, 2, 223–230. http://doi.org/10.17736/jowe.2015.arr04 (Original work published 2026)
Fidler, M., Lübben, R., & Becker, N. (2015). Capacity-Delay-Error Boundaries: A Composable Model of Sources and Systems. IEEE Trans. Wireless Commun., 14, 1280–1294. http://doi.org/10.1109/TWC.2014.2365782 (Original work published 2026)
Brandenburg, M., & Rebs, T. (2015). Sustainable supply chain management: a modeling perspective, 229(1), 213–252,. http://doi.org/10.1007/s10479-015-1853-1
Abstract
Nowadays, the integration of sustainability into supply chain management (SCM) is a key issue for ensuring corporate competitiveness in face of dynamic ecological and social environments. This paper reviews 185 journal publications of the last 20 years that formalize issues related to sustainable supply chain management (SSCM) in quantitative models. In a content analysis, modeling and SCM characteristics as well as sustainability and SSCM constructs are elaborated. The models are assessed numerically by counting frequencies of occurrence and by clustering the paper sample according to selected characteristics. The findings indicate that SSCM models predominantly focus on deterministic approaches and the integration of environmental aspects of sustainability while neglecting stochastic modeling techniques and the consideration of social factors. By now, comprehensive modeling approaches are most often employed on intra-organizational levels whereas broader application areas are assessed by less complex models. The integration of pressures and incentives of external stakeholders or the formalization of sustainable supplier management and sustainability risks are identified as future research perspectives. Furthermore, the interrelationships between the triple bottom line dimensions are to be scrutinized in greater detail in order to avoid focused optimization of selected sustainability criteria. Seven modeling guidelines are derived from the reviewed literature to facilitate future model-based SSCM research.
Kunz, A. L., Labes, A., Wiese, J., Bruhn, T., Bringmann, G., & Imhoff, J. F. (2015). Nature s Lab for Derivatization: New and Revised Structures of a Variety of Streptophenazines Produced by a Sponge-Derived Streptomyces Strain, Online-Ressource.
Brandenburg, M. (2015). Low carbon supply chain configuration for a new product – a goal programming approach. International Journal of Production Research, 53, 6588–6610. http://doi.org/10.1080/00207543.2015.1005761
Abstract
Green supply chain management and product innovation both have become sources of competitive advantage for companies from different industries. However, research on the configuration of green supply chains for new products represents a comparably new trend. In this paper, a goal programming approach is suggested to optimise the supply chain (SC) configuration for a new consumer product under consideration of economic and environmental criteria. The approach is illustrated by the case example of a fast moving consumer goods manufacturer. In this context, trade-offs between the ecologic factor of carbon emission, on the one hand, and financial value creation and customer service level on the other hand, are assessed in the deterministic analyses. The influence of long-term demand uncertainties is modelled in a scenario approach. It is observed that decentralised SC configurations enable carbon emission reduction without deteriorating the economic SC performance. Furthermore, it is detected that a focused economic optimisation strongly amplifies negative environmental impacts of demand uncertainties.
Bin Ali, N., Petersen, K., & De Fran\cca, B. B. N. (2015). Evaluation of simulation-assisted value stream mapping for software product development: Two industrial cases. Information and software technology, 68, 45–61.