@inproceedings{17370,
abstract = { We consider a natural extension to the metric uncapacitated Facility Location Problem (FLP) in which requests ask for different commodities out of a finite set \( S \) of commodities.
Ravi and Sinha (SODA 2004) introduced the model as the \emph{Multi-Commodity Facility Location Problem} (MFLP) and considered it an offline optimization problem.
The model itself is similar to the FLP: i.e., requests are located at points of a finite metric space and the task of an algorithm is to construct facilities and assign requests to facilities while minimizing the construction cost and the sum over all assignment distances.
In addition, requests and facilities are heterogeneous; they request or offer multiple commodities out of $S$.
A request has to be connected to a set of facilities jointly offering the commodities demanded by it.
In comparison to the FLP, an algorithm has to decide not only if and where to place facilities, but also which commodities to offer at each.
To the best of our knowledge we are the first to study the problem in its online variant in which requests, their positions and their commodities are not known beforehand but revealed over time.
We present results regarding the competitive ratio.
On the one hand, we show that heterogeneity influences the competitive ratio by developing a lower bound on the competitive ratio for any randomized online algorithm of \( \Omega ( \sqrt{|S|} + \frac{\log n}{\log \log n} ) \) that already holds for simple line metrics.
Here, \( n \) is the number of requests.
On the other side, we establish a deterministic \( \mathcal{O}(\sqrt{|S|} \cdot \log n) \)-competitive algorithm and a randomized \( \mathcal{O}(\sqrt{|S|} \cdot \frac{\log n}{\log \log n} ) \)-competitive algorithm.
Further, we show that when considering a more special class of cost functions for the construction cost of a facility, the competitive ratio decreases given by our deterministic algorithm depending on the function.},
author = {Castenow, Jannik and Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm},
booktitle = {Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures},
isbn = {9781450369350},
keyword = {Online Multi-Commodity Facility Location, Competitive Ratio, Online Optimization, Facility Location Problem},
title = {{The Online Multi-Commodity Facility Location Problem}},
doi = {10.1145/3350755.3400281},
year = {2020},
}
@article{17375,
author = {Zhou, Jiaqi and Khazaei, Mohammad and Ranjbar, Ahmad and Wang, Vei and Kühne, Thomas D. and Ohno, Kaoru and Kawazoe, Yoshiyuki and Liang, Yunye},
journal = {J. Mater. Chem. C},
pages = {5211--5221},
publisher = {The Royal Society of Chemistry},
title = {{Modulation of nearly free electron states in hydroxyl-functionalized MXenes: a first-principles study}},
doi = {10.1039/C9TC06837F},
volume = {8},
year = {2020},
}
@article{17382,
author = {Rengaraj, Varadarajan and Lass, Michael and Plessl, Christian and Kühne, Thomas D.},
issn = {2079-3197},
journal = {Computation},
number = {2},
pages = {39},
publisher = {MDPI AG},
title = {{Accurate Sampling with Noisy Forces from Approximate Computing}},
doi = {10.3390/computation8020039},
volume = {8},
year = {2020},
}
@article{16839,
author = {Sain, Basudeb and Zentgraf, Thomas},
issn = {2047-7538},
journal = {Light: Science & Applications},
pages = {67},
title = {{Metasurfaces help lasers to mode-lock}},
doi = {10.1038/s41377-020-0312-1},
volume = {9},
year = {2020},
}
@inproceedings{17399,
author = {Hardes, Tobias and Sommer, Christoph},
booktitle = {2019 IEEE Vehicular Networking Conference (VNC)},
isbn = {9781728145716},
title = {{Towards Heterogeneous Communication Strategies for Urban Platooning at Intersections}},
doi = {10.1109/vnc48660.2019.9062835},
year = {2020},
}
@inproceedings{17368,
author = {Vorbohle, Christian and Szopinski, Daniel and Kundisch, Dennis},
editor = {Shishkov, B.},
isbn = {978-3-030-52305-3},
location = {Potsdam, Germany},
publisher = {Springer},
title = {{Business Model Dependencies: Towards conceptualizing dependencies for extending modeling languages for business models}},
volume = {391},
year = {2020},
}
@inproceedings{16726,
author = {Razzaghi Kouchaksaraei, Hadi and Prasad Shivarpatna Venkatesh, Ashwin and Churi, Amey and Illian, Marvin and Karl, Holger},
booktitle = {European Conference on Networks and Communications (EUCNC 2020)},
title = {{Dynamic Provisioning of Network Services on Heterogeneous Resources}},
year = {2020},
}
@inproceedings{17407,
author = {Tornede, Alexander and Wever, Marcel Dominik and Hüllermeier, Eyke},
booktitle = {Discovery Science},
title = {{Extreme Algorithm Selection with Dyadic Feature Representation}},
year = {2020},
}
@article{17426,
abstract = {The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.},
author = {Hoffmann, Martin W. and Wildermuth, Stephan and Gitzel, Ralf and Boyaci, Aydin and Gebhardt, Jörg and Kaul, Holger and Amihai, Ido and Forg, Bodo and Suriyah, Michael and Leibfried, Thomas and Stich, Volker and Hicking, Jan and Bremer, Martin and Kaminski, Lars and Beverungen, Daniel and zur Heiden, Philipp and Tornede, Tanja},
issn = {1424-8220},
journal = {Sensors},
title = {{Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions}},
doi = {10.3390/s20072099},
year = {2020},
}
@article{17433,
author = {Wang, D. Q. and Reuter, Dirk and Wieck, A. D. and Hamilton, A. R. and Klochan, O.},
issn = {0003-6951},
journal = {Applied Physics Letters},
title = {{Two-dimensional lateral surface superlattices in GaAs heterostructures with independent control of carrier density and modulation potential}},
doi = {10.1063/5.0009462},
year = {2020},
}