@inproceedings{HoppmannSchwarz, author = {Hoppmann, Kai and Schwarz, Robert}, title = {Finding Maximum Minimum Cost Flows to Evaluate Gas Network Capacities}, series = {Operations Research Proceedings 2017}, booktitle = {Operations Research Proceedings 2017}, isbn = {978-3-319-89919-0}, doi = {10.1007/978-3-319-89920-6_46}, pages = {339 -- 346}, abstract = {In this article we consider the following problem arising in the context of scenario generation to evaluate the transport capacity of gas networks: In the Uncapacitated Maximum Minimum Cost Flow Problem (UMMCF) we are given a flow network where each arc has an associated nonnegative length and infinite capacity. Additionally, for each source and each sink a lower and an upper bound on its supply and demand are known, respectively. The goal is to find values for the supplies and demands respecting these bounds, such that the optimal value of the induced Minimum Cost Flow Problem is maximized, i.e., to determine a scenario with maximum transportmoment. In this article we propose two linear bilevel optimization models for UMMCF, introduce a greedy-style heuristic, and report on our first computational experiment.}, language = {en} } @article{SerranoSchwarzGleixner, author = {Serrano, Felipe and Schwarz, Robert and Gleixner, Ambros}, title = {On the relation between the extended supporting hyperplane algorithm and Kelley's cutting plane algorithm}, series = {Journal of Global Optimization}, volume = {78}, journal = {Journal of Global Optimization}, doi = {10.1007/s10898-020-00906-y}, pages = {161 -- 179}, abstract = {Recently, Kronqvist et al. (J Global Optim 64(2):249-272, 2016) rediscovered the supporting hyperplane algorithm of Veinott (Oper Res 15(1):147-152, 1967) and demonstrated its computational benefits for solving convex mixed integer nonlinear programs. In this paper we derive the algorithm from a geometric point of view. This enables us to show that the supporting hyperplane algorithm is equivalent to Kelley's cutting plane algorithm (J Soc Ind Appl Math 8(4):703-712, 1960) applied to a particular reformulation of the problem. As a result, we extend the applicability of the supporting hyperplane algorithm to convex problems represented by a class of general, not necessarily convex nor differentiable, functions.}, language = {en} } @misc{SerranoSchwarzGleixner, author = {Serrano, Felipe and Schwarz, Robert and Gleixner, Ambros}, title = {On the Relation between the Extended Supporting Hyperplane Algorithm and Kelley's Cutting Plane Algorithm}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-73253}, abstract = {Recently, Kronqvist et al. (2016) rediscovered the supporting hyperplane algorithm of Veinott (1967) and demonstrated its computational benefits for solving convex mixed-integer nonlinear programs. In this paper we derive the algorithm from a geometric point of view. This enables us to show that the supporting hyperplane algorithm is equivalent to Kelley's cutting plane algorithm applied to a particular reformulation of the problem. As a result, we extend the applicability of the supporting hyperplane algorithm to convex problems represented by general, not necessarily convex, differentiable functions that satisfy a mild condition.}, language = {en} } @misc{HillerKochScheweetal., author = {Hiller, Benjamin and Koch, Thorsten and Schewe, Lars and Schwarz, Robert and Schweiger, Jonas}, title = {A System to Evaluate Gas Network Capacities: Concepts and Implementation}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-67438}, abstract = {In 2005 the European Union liberalized the gas market with a disruptive change and decoupled trading of natural gas from its transport. The gas is now transported by independent so-called transmissions system operators or TSOs. The market model established by the European Union views the gas transmission network as a black box, providing shippers (gas traders and consumers) the opportunity to transport gas from any entry to any exit. TSOs are required to offer the maximum possible capacities at each entry and exit such that any resulting gas flow can be realized by the network. The revenue from selling these capacities more than one billion Euro in Germany alone, but overestimating the capacity might compromise the security of supply. Therefore, evaluating the available transport capacities is extremely important to the TSOs. This is a report on a large project in mathematical optimization, set out to develop a new toolset for evaluating gas network capacities. The goals and the challenges as they occurred in the project are described, as well as the developments and design decisions taken to meet the requirements.}, language = {en} } @article{HillerKochScheweetal., author = {Hiller, Benjamin and Koch, Thorsten and Schewe, Lars and Schwarz, Robert and Schweiger, Jonas}, title = {A System to Evaluate Gas Network Capacities: Concepts and Implementation}, series = {European Journal of Operational Research}, volume = {270}, journal = {European Journal of Operational Research}, number = {3}, pages = {797 -- 808}, abstract = {In 2005 the European Union liberalized the gas market with a disruptive change and decoupled trading of natural gas from its transport. The gas is now trans- ported by independent so-called transmissions system operators or TSOs. The market model established by the European Union views the gas transmission network as a black box, providing shippers (gas traders and consumers) the opportunity to transport gas from any entry to any exit. TSOs are required to offer the maximum possible capacities at each entry and exit such that any resulting gas flow can be realized by the network. The revenue from selling these capacities more than one billion Euro in Germany alone, but overestimating the capacity might compromise the security of supply. Therefore, evaluating the available transport capacities is extremely important to the TSOs. This is a report on a large project in mathematical optimization, set out to develop a new toolset for evaluating gas network capacities. The goals and the challenges as they occurred in the project are described, as well as the developments and design decisions taken to meet the requirements.}, language = {en} } @incollection{SchwarzLacalandraScheweetal., author = {Schwarz, R. and Lacalandra, F. and Schewe, L. and Bettinelli, A. and Vigo, D. and Bischi, A. and Parriani, T. and Martelli, E. and Vuik, K. and Lenz, R. and Madsen, H. and Blanco, I. and Guericke, D. and Y{\"u}ksel-Erg{\"u}n, I. and Zittel, J.}, title = {Network and Storage}, series = {Mathematical Optimization for Efficient and Robust Energy Networks}, volume = {4}, booktitle = {Mathematical Optimization for Efficient and Robust Energy Networks}, publisher = {Springer}, isbn = {978-3-030-57442-0}, doi = {https://doi.org/10.1007/978-3-030-57442-0_6}, abstract = {Natural gas is considered by many to be the most important energy source for the future. The objectives of energy commodities strategic problems can be mainly related to natural gas and deal with the definition of the "optimal" gas pipelines design which includes a number of related sub problems such as: Gas stations (compression) location and Gas storage locations, as well as compression station design and optimal operation.}, language = {en} }