@inproceedings{AltherrEdererSchaenzleetal.2017,
  author    = {Altherr, Lena and Ederer, Thorsten and Sch{\"a}nzle, Christian and Lorenz, Ulf and Pelz, Peter F.},
  title     = {Algorithmic system design using scaling and affinity laws},
  series = {Operations Research Proceedings 2015},
  booktitle = {Operations Research Proceedings 2015},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-42901-4},
  doi       = {10.1007/978-3-319-42902-1},
  pages     = {605 -- 611},
  year      = {2017},
  abstract  = {Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem.},
  language  = {en}
}
@inproceedings{MarcoFerrein2017,
  author    = {Marco, Heather G. and Ferrein, Alexander},
  title     = {AGNES: The African-German Network of Excellence in Science},
  series = {Proceedings of the 2nd Developing World Robotics Forum, Workshop at IEEE AFRICON 2017},
  booktitle = {Proceedings of the 2nd Developing World Robotics Forum, Workshop at IEEE AFRICON 2017},
  pages     = {1 -- 2},
  year      = {2017},
  language  = {en}
}
@inproceedings{SchifferFerrein2017,
  author    = {Schiffer, Stefan and Ferrein, Alexander},
  title     = {A System Layout for Cognitive Service Robots},
  series = {Cognitive Robot Architectures. Proceedings of EUCognition 2016},
  booktitle = {Cognitive Robot Architectures. Proceedings of EUCognition 2016},
  issn      = {1613-0073},
  pages     = {44 -- 45},
  year      = {2017},
  language  = {en}
}
@incollection{AltherrDoerigEdereretal.2017,
  author    = {Altherr, Lena and D{\"o}rig, Bastian and Ederer, Thorsten and Pelz, Peter Franz and Pfetsch, Marc and Wolf, Jan},
  title     = {A mixed-integer nonlinear program for the design of gearboxes},
  series = {Operations Research Proceedings 2016},
  booktitle = {Operations Research Proceedings 2016},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-55701-4},
  doi       = {10.1007/978-3-319-55702-1_31},
  pages     = {227 -- 233},
  year      = {2017},
  abstract  = {Gearboxes are mechanical transmission systems that provide speed and torque conversions from a rotating power source. Being a central element of the drive train, they are relevant for the efficiency and durability of motor vehicles. In this work, we present a new approach for gearbox design: Modeling the design problem as a mixed-integer nonlinear program (MINLP) allows us to create gearbox designs from scratch for arbitrary requirements and—given enough time—to compute provably globally optimal designs for a given objective. We show how different degrees of freedom influence the runtime and present an exemplary solution.},
  language  = {en}
}
@inproceedings{WalentaSchellekensFerreinetal.2017,
  author    = {Walenta, Robert and Schellekens, Twan and Ferrein, Alexander and Schiffer, Stefan},
  title     = {A decentralised system approach for controlling AGVs with ROS},
  series = {AFRICON, Proceedings},
  booktitle = {AFRICON, Proceedings},
  publisher = {IEEE},
  isbn      = {978-1-5386-2775-4},
  issn      = {2153-0033},
  doi       = {10.1109/AFRCON.2017.8095693},
  pages     = {1436 -- 1441},
  year      = {2017},
  language  = {en}
}