@incollection{StengerAltherrMuelleretal.2018,
  author    = {Stenger, David and Altherr, Lena and M{\"u}ller, Tankred and Pelz, Peter F.},
  title     = {Product family design optimization using model-based engineering techniques},
  series = {Operations Research Proceedings 2017},
  booktitle = {Operations Research Proceedings 2017},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-89919-0},
  doi       = {10.1007/978-3-319-89920-6_66},
  pages     = {495 -- 502},
  year      = {2018},
  abstract  = {Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.},
  language  = {en}
}
@article{SunAltherrPeietal.2018,
  author    = {Sun, Hui and Altherr, Lena and Pei, Ji and Pelz, Peter F. and Yuan, Shouqi},
  title     = {Optimal booster station design and operation under uncertain load},
  series = {Applied Mechanics and Materials},
  volume    = {885},
  journal   = {Applied Mechanics and Materials},
  publisher = {Trans Tech Publications},
  address   = {B{\"a}ch},
  issn      = {1662-7482},
  doi       = {10.4028/www.scientific.net/AMM.885.102},
  pages     = {102 -- 115},
  year      = {2018},
  abstract  = {Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the system's resilience can be engineered},
  language  = {en}
}