@inproceedings{AltherrPelzEdereretal.2017,
  author    = {Altherr, Lena and Pelz, Peter F. and Ederer, Thorsten and Pfetsch, Marc E.},
  title     = {Optimale Getriebe auf Knopfdruck: Gemischt-ganzzahlige nichtlineare Optimierung zur Entscheidungsunterst{\"u}tzung bei der Auslegung von Getrieben f{\"u}r Kraftfahrzeuge},
  series = {Antriebstechnisches Kolloquium ATK 2017},
  booktitle = {Antriebstechnisches Kolloquium ATK 2017},
  editor    = {Jacobs, Georg},
  isbn      = {9783743148970},
  pages     = {313 -- 325},
  year      = {2017},
  language  = {de}
}
@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{AltherrEdererFarnetaneetal.2017,
  author    = {Altherr, Lena and Ederer, Thorsten and Farnetane, Lucas S. and P{\"o}ttgen, Philipp and Verg{\´e}, Angela and Pelz, Peter F.},
  title     = {Multicriterial design of a hydrostatic transmission system via mixed-integer programming},
  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_41},
  pages     = {301 -- 307},
  year      = {2017},
  abstract  = {In times of planned obsolescence the demand for sustainability keeps growing. Ideally, a technical system is highly reliable, without failures and down times due to fast wear of single components. At the same time, maintenance should preferably be limited to pre-defined time intervals. Dispersion of load between multiple components can increase a system's reliability and thus its availability inbetween maintenance points. However, this also results in higher investment costs and additional efforts due to higher complexity. Given a specific load profile and resulting wear of components, it is often unclear which system structure is the optimal one. Technical Operations Research (TOR) finds an optimal structure balancing availability and effort. We present our approach by designing a hydrostatic transmission system.},
  language  = {en}
}