@misc{GleixnerBastubbeEifleretal.2018, author = {Gleixner, Ambros and Bastubbe, Michael and Eifler, Leon and Gally, Tristan and Gamrath, Gerald and Gottwald, Robert Lion and Hendel, Gregor and Hojny, Christopher and Koch, Thorsten and L{\"u}bbecke, Marco and Maher, Stephen J. and Miltenberger, Matthias and M{\"u}ller, Benjamin and Pfetsch, Marc and Puchert, Christian and Rehfeldt, Daniel and Schl{\"o}sser, Franziska and Schubert, Christoph and Serrano, Felipe and Shinano, Yuji and Viernickel, Jan Merlin and Walter, Matthias and Wegscheider, Fabian and Witt, Jonas T. and Witzig, Jakob}, title = {The SCIP Optimization Suite 6.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-69361}, year = {2018}, abstract = {The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders' decomposition in a generic framework. GCG's detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders' framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.}, language = {en} } @inproceedings{SchlosserWernerSchlenketal.2014, author = {Schlosser, Michael and Werner, Axel and Schlenk, Ralph and Jungel, Tobias and Lange, Christoph}, title = {Demonstrating energy-efficiency improvements in load-adaptive dynamic multilayer optical networks}, volume = {248}, booktitle = {Tagungsband Photonische Netze}, publisher = {VDE-Verlag}, pages = {42 -- 46}, year = {2014}, abstract = {The discussion about sustainability and climate change as well as the energy cost perspective of network operators gives increasing attention to the energy efficiency of telecommunication networks. A promising way to improve the energy efficiency of such networks is the load-adaptive operation in which the network capacity is adjusted to the actual timevarying traffic transport needs. In this paper the concept of load-adaptive operation in the core network is explained, with the respective underlying optical network and the associated mathematical optimization. Within the DESI project a demonstrator has been realized with a commercially available WDM/OTN system. As results, concrete proven power and energy savings and the projected savings for a nationwide multilayer core network are reported.}, language = {en} }