@misc{GroetschelMartinWeismantel1992, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Packing Steiners Trees: A Cutting Plane Algorithm and Computational Results.}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-792}, number = {SC-92-09}, year = {1992}, abstract = {In this paper we describe a cutting plane algorithm for the Steiner tree packing problem. We use our algorithm to solve some switchbox routing problems of VLSI-design and report on our computational experience. This includes a brief discussion of separation algorithms, a new LP-based primal heuristic and implementation details. The paper is based on the polyhedral theory for the Steiner tree packing polyhedron developed in our companion paper SC 92-8 and meant to turn this theory into an algorithmic tool for the solution of practical problems.}, language = {en} } @misc{FerreiraGroetschelKiefletal.1993, author = {Ferreira, Carlos E. and Gr{\"o}tschel, Martin and Kiefl, Stefan and Krispenz, Ludwig and Martin, Alexander and Weismantel, Robert}, title = {Some Integer Programs Arising in the Design of Main Frame Computers.}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-957}, number = {SC-92-25}, year = {1993}, abstract = {In this paper we describe and discuss a problem that arises in the (global) design of a main frame computer. The task is to assign certain functional units to a given number of so called multi chip modules or printed circuit boards taking into account many technical constraints and minimizing a complex objective function. We describe the real world problem. A thorough mathematical modelling of all aspects of this problem results in a rather complicated integer program that seems to be hopelessly difficult -- at least for the present state of integer programming technology. We introduce several relaxations of the general model, which are also \$NP\$-hard, but seem to be more easily accessible. The mathematical relations between the relaxations and the exact formulation of the problem are discussed as well.}, language = {en} } @misc{GroetschelMartinWeismantel1992, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Routing in Grid Graphs by Cutting Planes.}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-967}, number = {SC-92-26}, year = {1992}, abstract = {{\def\N{{\cal N}} \def\R{\hbox{\rm I\kern-2pt R}} \def\MN{{\rm I\kern-2pt N}} In this paper we study the following problem, which we call the weighted routing problem. Let be given a graph \$G=(V,E)\$ with non-negative edge weights \$w_e\in\R_+\$ and integer edge capacities \$c_e\in\MN\$ and let \$\N=\{T_1,\ldots,T_N\}\$, \$N\ge 1\$, be a list of node sets. The weighted routing problem consists in finding edge sets \$S_1,\ldots,S_N\$ such that, for each \$k\in\{1,\ldots,N\}\$, the subgraph \$(V(S_k),S_k)\$ contains an \$[s,t]\$-path for all \$s,t\in T_k\$, at most \$c_e\$ of these edge sets use edge \$e\$ for each \$e\in E\$, and such that the sum of the weights of the edge sets is minimal. Our motivation for studying this problem arises from the routing problem in VLSI-design, where given sets of points have to be connected by wires. We consider the weighted routing problem from a polyhedral point of view. We define an appropriate polyhedron and try to (partially) describe this polyhedron by means of inequalities. We briefly sketch our separation algorithms for some of the presented classes of inequalities. Based on these separation routines we have implemented a branch and cut algorithm. Our algorithm is applicable to an important subclass of routing problems arising in VLSI-design, namely to problems where the underlying graph is a grid graph and the list of node sets is located on the outer face of the grid. We report on our computational experience with this class of problem instances.}}, language = {en} } @misc{GroetschelMartinWeismantel1992, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Packing Steiner Trees: Further Facets.}, doi = {10.1006/eujc.1996.0004}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-975}, number = {SC-93-01}, year = {1992}, abstract = {In this paper we continue the investigations in [GMW92a] for the \def\sbppo{Steiner tree packing polyhedron} \sbppo. We present several new classes of valid inequalities and give sufficient (and necessary) conditions for these inequalities to be facet-defining. It is intended to incorporate these inequalities into an existing cutting plane algorithm that is applicable to practical problems arising in the design of electronic circuits.}, language = {en} } @misc{GroetschelMartinWeismantel1992, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Packing Steiner Trees: Separation Algorithms.}, doi = {10.1137/S0895480193258716}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-984}, number = {SC-93-02}, year = {1992}, abstract = {In this paper we investigate separation problems for classes of inequalities valid for the polytope associated with the Steiner tree packing problem, a problem that arises, e.~g., in VLSI routing. The separation problem for Steiner partition inequalities is \${\cal N}\hskip-2pt{\cal P}\$-hard in general. We show that it can be solved in polynomial time for those instances that come up in switchbox routing. Our algorithm uses dynamic programming techniques. These techniques are also applied to the much more complicated separation problem for alternating cycle inequalities. In this case we can compute in polynomial time, given some point \$y\$, a lower bound for the gap \$\alpha-a^Ty\$ over all alternating cycle inequalities \$a^Tx\ge\alpha\$. This gives rise to a very effective separation heuristic. A by-product of our algorithm is the solution of a combinatorial optimization problem that is interesting in its own right: Find a shortest path in a graph where the ``length'' of a path is its usual length minus the length of its longest edge.}, language = {en} } @misc{BorndoerferEisenblaetterGroetscheletal.1997, author = {Bornd{\"o}rfer, Ralf and Eisenbl{\"a}tter, Andreas and Gr{\"o}tschel, Martin and Martin, Alexander}, title = {Frequency Assignment in Cellular Phone Networks}, doi = {10.1023/A:1018908907763}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-3044}, number = {SC-97-35}, year = {1997}, abstract = {We present a graph-theoretic model for the \emph{frequency assignment problem} in Cellular Phone Networks: Obeying several technical and legal restrictions, frequencies have to be assigned to transceivers so that interference is as small as possible. This optimization problem is NP-hard. Good approximation cannot be guaranteed, unless P = NP. We describe several assignment heuristics. These heuristics are simple and not too hard to implement. We give an assessment of the heuristics' efficiency and practical usefulness. For this purpose, typical instances of frequency assignment problems with up to 4240 transceivers and 75 frequencies of a German cellular phone network operator are used. The results are satisfying from a practitioner's point of view. The best performing heuristics were integrated into a network planning system used in practice.}, language = {en} } @misc{BrunsGubeladzeHenketal.1998, author = {Bruns, Winfried and Gubeladze, Joseph and Henk, Martin and Martin, Alexander and Weismantel, Robert}, title = {A counterexample to an integer analogue of Caratheodorys theorem}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-3718}, number = {SC-98-28}, year = {1998}, abstract = {For \$n\geq 6\$ we provide a counterexample to the conjecture that every integral vector of a \$n\$-dimensional integral polyhedral pointed cone \$C\$ can be written as a nonnegative integral combination of at most \$n\$ elements of the Hilbert basis of \$C\$. In fact, we show that in general at least \$\lfloor 7/6 \cdot n \rfloor\$ elements of the Hilbert basis are needed.}, language = {en} } @article{AignerClarnerLiersetal.2021, author = {Aigner, Kevin-Martin and Clarner, Jan-Patrick and Liers, Frauke and Martin, Alexander}, title = {Robust Approximation of Chance Constrained DC Optimal Power Flow under Decision-Dependent Uncertainty}, journal = {European Journal of Operational Research}, year = {2021}, abstract = {We propose a mathematical optimization model and its solution for joint chance constrained DC Optimal Power Flow. In this application, it is particularly important that there is a high probability of transmission limits being satisfied, even in the case of uncertain or fluctuating feed-in from renewable energy sources. In critical network situations where the network risks overload, renewable energy feed-in has to be curtailed by the transmission system operator (TSO). The TSO can reduce the feed-in in discrete steps at each network node. The proposed optimization model minimizes curtailment while ensuring that there is a high probability of transmission limits being maintained. The latter is modeled via (joint) chance constraints that are computationally challenging. Thus, we propose a solution approach based on the robust safe approximation of these constraints. Hereby, probabilistic constraints are replaced by robust constraints with suitably defined uncertainty sets constructed from historical data. The ability to discretely control the power feed-in then leads to a robust optimization problem with decision-dependent uncertainties, i.e. the uncertainty sets depend on decision variables. We propose an equivalent mixed-integer linear reformulation for box uncertainties with the exact linearization of bilinear terms. Finally, we present numerical results for different test cases from the Nesta archive, as well as for a real network. We consider the discrete curtailment of solar feed-in, for which we use real-world weather and network data. The experimental tests demonstrate the effectiveness of this method and run times are very fast. Moreover, on average the calculated robust solutions only lead to a small increase in curtailment, when compared to nominal solutions.}, language = {en} } @article{KochSchmidtHilleretal.2020, author = {Koch, Thorsten and Schmidt, Martin and Hiller, Benjamin and Pfetsch, Marc and Geißler, Bj{\"o}rn and Henrion, Ren{\´e} and Joormann, Imke and Martin, Alexander and Morsi, Antonio and R{\"o}misch, Werner and Schewe, Lars and Schultz, R{\"u}diger}, title = {Capacity Evaluation for Large-Scale Gas Networks}, volume = {35}, journal = {German Success Stories in Industrial Mathematics}, isbn = {978-3-030-81454-0}, doi = {10.1007/978-3-030-81455-7}, pages = {23 -- 28}, year = {2020}, language = {en} } @misc{BorndoerferEisenblaetterGroetscheletal.1998, author = {Bornd{\"o}rfer, Ralf and Eisenbl{\"a}tter, Andreas and Gr{\"o}tschel, Martin and Martin, Alexander}, title = {The Orientation Model for Frequency Assignment Problems}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-5627}, number = {TR-98-01}, year = {1998}, abstract = {Mobile telecommunication systems establish a large number of communication links with a limited number of available frequencies; reuse of the same or adjacent frequencies on neighboring links causes interference. The task to find an assignment of frequencies to channels with minimal interference is the frequency assignment problem. The frequency assignment problem is usually treated as a graph coloring problem where the number of colors is minimized, but this approach does not model interference minimization correctly. We give in this paper a new integer programming formulation of the frequency assignment problem, the orientation model, and develop a heuristic two-stage method to solve it. The algorithm iteratively solves an outer and an inner optimization problem. The outer problem decides for each pair of communication links which link gets the higher frequency and leads to an acyclic subdigraph problem with additional longest path restrictions. The inner problem to find an optimal assignment respecting an orientation leads to a min-cost flow problem.}, language = {en} } @article{GroetschelMartinWeismantel1996, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Packing Steiner trees: Polyhedral Investigations}, volume = {72}, journal = {Mathematical Programming, Series A}, number = {2}, doi = {10.1007/BF02592085}, pages = {101 -- 123}, year = {1996}, language = {en} } @article{GroetschelMartinWeismantel1996, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Optimum Path Packing on Wheels}, volume = {31}, journal = {Computers and Mathematics with Applications}, number = {11}, publisher = {Elsevier}, pages = {23 -- 35}, year = {1996}, language = {en} } @article{BorndoerferEisenblaetterGroetscheletal.1998, author = {Bornd{\"o}rfer, Ralf and Eisenbl{\"a}tter, Andreas and Gr{\"o}tschel, Martin and Martin, Alexander}, title = {Frequency assignment in cellular phone networks}, volume = {76}, journal = {Annals of Operations Research}, publisher = {J. C. Baltzer AG, Science Publishers}, doi = {10.1023/A:1018908907763}, pages = {73 -- 93}, year = {1998}, language = {en} } @article{GroetschelMartinWeismantel1996, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Packing Steiner trees: a cutting plane algorithm and computational results}, volume = {72}, journal = {Mathematical Programming, Series A}, number = {2}, doi = {10.1007/BF02592086}, pages = {125 -- 145}, year = {1996}, language = {en} } @article{GroetschelMartinWeismantel1997, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {The Steiner tree packing problem in VLSI design}, volume = {78}, journal = {Mathematical Programming}, number = {2}, pages = {265 -- 281}, year = {1997}, language = {en} } @inproceedings{BirkhoferFuegenschuhGuentheretal.2006, author = {Birkhofer, Herbert and F{\"u}genschuh, Armin and G{\"u}nther, Ute and Junglas, Daniel and Martin, Alexander and Sauer, Thorsten and Ulbrich, Stefan and W{\"a}ldele, Martin and Walter, Stephan}, title = {Topology- and shape-optimization of branched sheet metal products}, booktitle = {Operations Research Proceedings}, editor = {Haasis, Hans-Dietrich and Kopfer, Herbert and Sch{\"o}nberger, J{\"o}rn}, pages = {327 -- 336}, year = {2006}, language = {en} } @inproceedings{GroetschelMartinWeismantel1993, author = {Gr{\"o}tschel, Martin and Martin, Alexander and Weismantel, Robert}, title = {Routing in grid graphs by cutting planes}, booktitle = {Integer Programming and Combinatorial Optimization. Proceedings of a Conference held at Centro Ettore Majorana, Erice, Italy, April 29 - May 1, 1993}, editor = {Rinaldi, Giovanni and Wolsey, Laurence}, publisher = {Librarian CORE}, address = {Louvain-la-Neuve}, pages = {447 -- 461}, year = {1993}, language = {en} } @inproceedings{BirkhoferFuegenschuhMartinetal.2007, author = {Birkhofer, Herbert and F{\"u}genschuh, Armin and Martin, Alexander and W{\"a}ldele, Martin}, title = {Algorithmenbasierte Produktentwicklung f{\"u}r integrale Blechbauweisen h{\"o}herer Verzweigungsordnung}, booktitle = {Optimierung in der Produktentwicklung, 5. Geimeinsames Kolloquium Konstruktionstechnik}, year = {2007}, language = {en} } @article{PfetschFuegenschuhGeissleretal.2014, author = {Pfetsch, Marc and F{\"u}genschuh, Armin and Geißler, Bj{\"o}rn and Geißler, Nina and Gollmer, Ralf and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Martin, Alexander and Morsi, Antonio and R{\"o}vekamp, Jessica and Schewe, Lars and Schmidt, Martin and Schultz, R{\"u}diger and Schwarz, Robert and Schweiger, Jonas and Stangl, Claudia and Steinbach, Marc and Vigerske, Stefan and Willert, Bernhard}, title = {Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions}, journal = {Optimization Methods and Software}, publisher = {Taylor \& Francis}, doi = {10.1080/10556788.2014.888426}, year = {2014}, abstract = {In this article we investigate methods to solve a fundamental task in gas transportation, namely the validation of nomination problem: Given a gas transmission network consisting of passive pipelines and active, controllable elements and given an amount of gas at every entry and exit point of the network, find operational settings for all active elements such that there exists a network state meeting all physical, technical, and legal constraints. We describe a two-stage approach to solve the resulting complex and numerically difficult feasibility problem. The first phase consists of four distinct algorithms applying linear, and methods for complementarity constraints to compute possible settings for the discrete decisions. The second phase employs a precise continuous programming model of the gas network. Using this setup, we are able to compute high quality solutions to real-world industrial instances that are significantly larger than networks that have appeared in the mathematical programming literature before.}, language = {en} } @article{FuegenschuhGeisslerGollmeretal.2013, author = {F{\"u}genschuh, Armin and Geißler, Bj{\"o}rn and Gollmer, Ralf and Hayn, Christine and Henrion, Ren{\´e} and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Martin, Alexander and Mirkov, Radoslava and Morsi, Antonio and R{\"o}misch, Werner and R{\"o}vekamp, Jessica and Schewe, Lars and Schmidt, Martin and Schultz, R{\"u}diger and Schwarz, Robert and Schweiger, Jonas and Stangl, Claudia and Steinbach, Marc and Willert, Bernhard}, title = {Mathematical optimization for challenging network planning problems in unbundled liberalized gas markets}, volume = {5}, journal = {Energy Systems}, number = {3}, publisher = {Springer Berlin Heidelberg}, address = {Berlin}, doi = {10.1007/s12667-013-0099-8}, pages = {449 -- 473}, year = {2013}, abstract = {The recently imposed new gas market liberalization rules in Germany lead to a change of business of gas network operators. While previously network operator and gas vendor were united, they were forced to split up into independent companies. The network has to be open to any other gas trader at the same conditions, and free network capacities have to be identified and publicly offered in a non-discriminatory way. We discuss how these changing paradigms lead to new and challenging mathematical optimization problems. This includes the validation of nominations, that asks for the decision if the network's capacity is sufficient to transport a specific amount of flow, the verification of booked capacities and the detection of available freely allocable capacities, and the topological extension of the network with new pipelines or compressors in order to increase its capacity. In order to solve each of these problems and to provide meaningful results for the practice, a mixture of different mathematical aspects have to be addressed, such as combinatorics, stochasticity, uncertainty, and nonlinearity. Currently, no numerical solver is available that can deal with such blended problems out-of-the-box. The main goal of our research is to develop such a solver, that moreover is able to solve instances of realistic size. In this article, we describe the main ingredients of our prototypical software implementations.}, language = {en} }