@misc{GleixnerSteffy2019, author = {Gleixner, Ambros and Steffy, Daniel}, title = {Linear Programming using Limited-Precision Oracles}, issn = {1438-0064}, doi = {10.1007/s10107-019-01444-6}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-75316}, year = {2019}, abstract = {Since the elimination algorithm of Fourier and Motzkin, many different methods have been developed for solving linear programs. When analyzing the time complexity of LP algorithms, it is typically either assumed that calculations are performed exactly and bounds are derived on the number of elementary arithmetic operations necessary, or the cost of all arithmetic operations is considered through a bit-complexity analysis. Yet in practice, implementations typically use limited-precision arithmetic. In this paper we introduce the idea of a limited-precision LP oracle and study how such an oracle could be used within a larger framework to compute exact precision solutions to LPs. Under mild assumptions, it is shown that a polynomial number of calls to such an oracle and a polynomial number of bit operations, is sufficient to compute an exact solution to an LP. This work provides a foundation for understanding and analyzing the behavior of the methods that are currently most effective in practice for solving LPs exactly.}, language = {en} } @misc{SerranoMunoz2019, author = {Serrano, Felipe and Mu{\~n}oz, Gonzalo}, title = {Maximal Quadratic-Free Sets}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-76922}, year = {2019}, abstract = {The intersection cut paradigm is a powerful framework that facilitates the generation of valid linear inequalities, or cutting planes, for a potentially complex set S. The key ingredients in this construction are a simplicial conic relaxation of S and an S-free set: a convex zone whose interior does not intersect S. Ideally, such S-free set would be maximal inclusion-wise, as it would generate a deeper cutting plane. However, maximality can be a challenging goal in general. In this work, we show how to construct maximal S-free sets when S is defined as a general quadratic inequality. Our maximal S-free sets are such that efficient separation of a vertex in LP-based approaches to quadratically constrained problems is guaranteed. To the best of our knowledge, this work is the first to provide maximal quadratic-free sets.}, language = {en} } @inproceedings{DiakonikolasCardereraPokutta2019, author = {Diakonikolas, Jelena and Carderera, Alejandro and Pokutta, Sebastian}, title = {Breaking the Curse of Dimensionality (Locally) to Accelerate Conditional Gradients}, booktitle = {OPTML Workshop Paper}, arxiv = {http://arxiv.org/abs/1906.07867}, year = {2019}, language = {en} } @inproceedings{CombettesPokutta2019, author = {Combettes, Cyrille W. and Pokutta, Sebastian}, title = {Blended Matching Pursuit}, booktitle = {Proceedings of NeurIPS}, arxiv = {http://arxiv.org/abs/1904.12335}, year = {2019}, language = {en} } @inproceedings{PokuttaSinghTorrico2019, author = {Pokutta, Sebastian and Singh, M. and Torrico, A.}, title = {On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness}, booktitle = {OPTML Workshop Paper}, year = {2019}, language = {en} } @misc{BorndoerferTeschSagnol2019, author = {Bornd{\"o}rfer, Ralf and Tesch, Alexander and Sagnol, Guillaume}, title = {Algorithmen unterst{\"u}tzen OP-Planung}, journal = {Management \& Krankenhaus}, number = {12}, publisher = {Wiley}, pages = {20}, year = {2019}, abstract = {Mathematische Algorithmen k{\"o}nnen durch Vorhersage von Unsicherheiten optimierte OP-Pl{\"a}ne berechnen, sodass mehrere Zielkriterien wie {\"U}berstunden, Wartezeit und Ausf{\"a}lle im OP minimiert werden.}, language = {de} } @misc{BeckerHiller2019, author = {Becker, Kai-Helge and Hiller, Benjamin}, title = {Improved optimization models for potential-driven network flow problems via ASTS orientations}, issn = {1438-0064}, doi = {10.12752/7534}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-75347}, year = {2019}, abstract = {The class of potential-driven network flow problems provides important models for a range of infrastructure networks that lead to hard-to-solve MINLPs in real-world applications. On large-scale meshed networks the relaxations usually employed are rather weak due to cycles in the network. To address this situation, we introduce the concept of ASTS orientations, a generalization of bipolar orientations, as a combinatorial relaxation of feasible solutions of potential-driven flow problems, study their structure, and show how they can be used to strengthen existing relaxations and thus provide improved optimization models. Our computational results indicate that ASTS orientations can be used to derive much stronger bounds on the flow variables than existing bound tightening methods and to yield significant performance improvements for an existing state-of-the-art MILP model for large-scale gas networks.}, language = {en} } @inproceedings{GrimmBorndoerferReutheretal.2019, author = {Grimm, Boris and Bornd{\"o}rfer, Ralf and Reuther, Markus and Schlechte, Thomas}, title = {A Cut Separation Approach for the Rolling Stock Rotation Problem with Vehicle Maintenance}, volume = {75}, booktitle = {19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)}, editor = {Cacchiani, Valentina and Marchetti-Spaccamela, Alberto}, publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik}, address = {Dagstuhl, Germany}, doi = {10.4230/OASIcs.ATMOS.2019.1}, pages = {1:1 -- 1:12}, year = {2019}, abstract = {For providing railway services the company's railway rolling stock is one if not the most important ingredient. It decides about the number of passenger or cargo trips the company can offer, about the quality a passenger experiences the train ride and it is often related to the image of the company itself. Thus, it is highly desired to have the available rolling stock in the best shape possible. Moreover, in many countries, as Germany where our industrial partner DB Fernverkehr AG (DBF) is located, laws enforce regular vehicle inspections to ensure the safety of the passengers. This leads to rolling stock optimization problems with complex rules for vehicle maintenance. This problem is well studied in the literature for example see [Mar{\´o}ti and Kroon, 2005; G{\´a}bor Mar{\´o}ti and Leo G. Kroon, 2007], or [Cordeau et al., 2001] for applications including vehicle maintenance. The contribution of this paper is a new algorithmic approach to solve the Rolling Stock Rotation Problem for the ICE high speed train fleet of DBF with included vehicle maintenance. It is based on a relaxation of a mixed integer linear programming model with an iterative cut generation to enforce the feasibility of a solution of the relaxation in the solution space of the original problem. The resulting mixed integer linear programming model is based on a hypergraph approach presented in [Ralf Bornd{\"o}rfer et al., 2015]. The new approach is tested on real world instances modeling different scenarios for the ICE high speed train network in Germany and compared to the approaches of [Reuther, 2017] that are in operation at DB Fernverkehr AG. The approach shows a significant reduction of the run time to produce solutions with comparable or even better objective function values.}, language = {en} } @incollection{BennerGrundelHimpeetal.2019, author = {Benner, Peter and Grundel, Sara and Himpe, Christian and Huck, Christoph and Streubel, Tom and Tischendorf, Caren}, title = {Gas Network Benchmark Models}, booktitle = {Applications of Differential-Algebraic Equations: Examples and Benchmarks}, publisher = {Springer International Publishing}, isbn = {978-3-030-03718-5}, doi = {10.1007/11221_2018_5}, pages = {171 -- 197}, year = {2019}, abstract = {The simulation of gas transportation networks becomes increasingly more important as its use-cases broaden to more complex applications. Classically, the purpose of the gas network was the transportation of predominantly natural gas from a supplier to the consumer for long-term scheduled volumes. With the rise of renewable energy sources, gas-fired power plants are often chosen to compensate for the fluctuating nature of the renewables, due to their on-demand power generation capability. Such an only short-term plannable supply and demand setting requires sophisticated simulations of the gas network prior to the dispatch to ensure the supply of all customers for a range of possible scenarios and to prevent damages to the gas network. In this work we describe the modeling of gas networks and present benchmark systems to test implementations and compare new or extended models.}, language = {en} } @misc{WitzigGleixner2019, author = {Witzig, Jakob and Gleixner, Ambros}, title = {Conflict-Driven Heuristics for Mixed Integer Programming}, issn = {1438-0064}, doi = {10.1287/ijoc.2020.0973}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-72204}, year = {2019}, abstract = {Two essential ingredients of modern mixed-integer programming (MIP) solvers are diving heuristics that simulate a partial depth-first search in a branch-and-bound search tree and conflict analysis of infeasible subproblems to learn valid constraints. So far, these techniques have mostly been studied independently: primal heuristics under the aspect of finding high-quality feasible solutions early during the solving process and conflict analysis for fathoming nodes of the search tree and improving the dual bound. Here, we combine both concepts in two different ways. First, we develop a diving heuristic that targets the generation of valid conflict constraints from the Farkas dual. We show that in the primal this is equivalent to the optimistic strategy of diving towards the best bound with respect to the objective function. Secondly, we use information derived from conflict analysis to enhance the search of a diving heuristic akin to classical coefficient diving. The computational performance of both methods is evaluated using an implementation in the source-open MIP solver SCIP. Experiments are carried out on publicly available test sets including Miplib 2010 and Cor@l.}, language = {en} } @article{RehfeldtKoch2019, author = {Rehfeldt, Daniel and Koch, Thorsten}, title = {Combining NP-Hard Reduction Techniques and Strong Heuristics in an Exact Algorithm for the Maximum-Weight Connected Subgraph Problem}, volume = {29}, journal = {SIAM Journal on Optimization}, number = {1}, publisher = {Society for Industrial and Applied Mathematics}, doi = {10.1137/17M1145963}, pages = {369 -- 398}, year = {2019}, abstract = {Borne out of a surprising variety of practical applications, the maximum-weight connected subgraph problem has attracted considerable interest during the past years. This interest has not only led to notable research on theoretical properties, but has also brought about several (exact) solvers-with steadily increasing performance. Continuing along this path, the following article introduces several new algorithms such as reduction techniques and heuristics and describes their integration into an exact solver. The new methods are evaluated with respect to both their theoretical and practical properties. Notably, the new exact framework allows to solve common problem instances from the literature faster than all previous approaches. Moreover, one large-scale benchmark instance from the 11th DIMACS Challenge can be solved for the first time to optimality and the primal-dual gap for two other ones can be significantly reduced.}, language = {en} } @inproceedings{AndersonHiller2019, author = {Anderson, Lovis and Hiller, Benjamin}, title = {A Sweep-Plane Algorithm for the Computation of the Volume of a Union of Polytopes}, volume = {Operations Research Proceedings}, booktitle = {Operations Research Proceedings 2018}, doi = {10.1007/978-3-030-18500-8_12}, year = {2019}, abstract = {Optimization models often feature disjunctions of polytopes as submodels. Such a disjunctive set is initially at best) relaxed to its convex hull, which is then refined by branching. To measure the error of the convex relaxation, the (relative) difference between the volume of the convex hull and the volume of the disjunctive set may be used. This requires a method to compute the volume of the disjunctive set. We propose a revised variant of an old algorithm by Bieri and Nef (1983) for this purpose. The algorithm uses a sweep-plane to incrementally calculate the volume of the disjunctive set as a function of the offset parameter of the sweep-plane.}, language = {en} } @article{FuriniTraversiBelottietal.2019, author = {Furini, Fabio and Traversi, Emiliano and Belotti, Pietro and Frangioni, Antonio and Gleixner, Ambros and Gould, Nick and Liberti, Leo and Lodi, Andrea and Misener, Ruth and Mittelmann, Hans and Sahinidis, Nikolaos V. and Vigerske, Stefan and Wiegele, Angelika}, title = {QPLIB: A Library of Quadratic Programming Instances}, volume = {11}, journal = {Mathematical Programming Computation}, number = {2}, doi = {10.1007/s12532-018-0147-4}, pages = {237 -- 265}, year = {2019}, abstract = {This paper describes a new instance library for Quadratic Programming (QP), i.e., the family of continuous and (mixed)-integer optimization problems where the objective function, the constrains, or both are quadratic. QP is a very diverse class of problems, comprising sub-classes of problems ranging from trivial to undecidable. This diversity is reflected in the variety of solution methods for QP, ranging from entirely combinatorial ones to completely continuous ones, including many for which both aspects are fundamental. Selecting a set of instances of QP that is at the same time not overwhelmingly onerous but sufficiently challenging for the many different interested communities is therefore important. We propose a simple taxonomy for QP instances that leads to a systematic problem selection mechanism. We then briefly survey the field of QP, giving an overview of theory, methods and solvers. Finally, we describe how the library was put together, and detail its final contents.}, language = {en} } @article{WeberSagerGleixner2019, author = {Weber, Tobias and Sager, Sebastian and Gleixner, Ambros}, title = {Solving Quadratic Programs to High Precision using Scaled Iterative Refinement}, volume = {11}, journal = {Mathematical Programming Computation}, publisher = {Springer Berlin Heidelberg}, doi = {10.1007/s12532-019-00154-6}, pages = {421 -- 455}, year = {2019}, abstract = {Quadratic optimization problems (QPs) are ubiquitous, and solution algorithms have matured to a reliable technology. However, the precision of solutions is usually limited due to the underlying floating-point operations. This may cause inconveniences when solutions are used for rigorous reasoning. We contribute on three levels to overcome this issue. First, we present a novel refinement algorithm to solve QPs to arbitrary precision. It iteratively solves refined QPs, assuming a floating-point QP solver oracle. We prove linear convergence of residuals and primal errors. Second, we provide an efficient implementation, based on SoPlex and qpOASES that is publicly available in source code. Third, we give precise reference solutions for the Maros and M{\´e}sz{\´a}ros benchmark library.}, language = {en} } @article{RehfeldtKochMaher2019, author = {Rehfeldt, Daniel and Koch, Thorsten and Maher, Stephen J.}, title = {Reduction Techniques for the Prize-Collecting Steiner Tree Problem and the Maximum-Weight Connected Subgraph Problem}, volume = {73}, journal = {Networks}, edition = {2}, publisher = {Wiley}, doi = {10.1002/net.21857}, pages = {206 -- 233}, year = {2019}, abstract = {The concept of reduction has frequently distinguished itself as a pivotal ingredient of exact solving approaches for the Steiner tree problem in graphs. In this paper we broaden the focus and consider reduction techniques for three Steiner problem variants that have been extensively discussed in the literature and entail various practical applications: The prize-collecting Steiner tree problem, the rooted prize-collecting Steiner tree problem and the maximum-weight connected subgraph problem. By introducing and subsequently deploying numerous new reduction methods, we are able to drastically decrease the size of a large number of benchmark instances, already solving more than 90 percent of them to optimality. Furthermore, we demonstrate the impact of these techniques on exact solving, using the example of the state-of-the-art Steiner problem solver SCIP-Jack.}, language = {en} }