@article{PfetschFuegenschuhGeissleretal., 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}, series = {Optimization Methods and Software}, journal = {Optimization Methods and Software}, publisher = {Taylor \& Francis}, doi = {10.1080/10556788.2014.888426}, 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} } @inproceedings{MartinGeisslerHeynetal.2011, author = {Martin, Alexander and Geißler, Bj{\"o}rn and Heyn, Christine and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Morsi, Antonio and Pfetsch, Marc and Schewe, Lars and Schmidt, Martin and Schultz, R{\"u}diger and Schwarz, Robert and Schweiger, Jonas and Steinbach, Marc and Willert, Bernhard}, title = {Optimierung Technischer Kapazit{\"a}ten in Gasnetzen}, series = {Optimierung in der Energiewirtschaft}, booktitle = {Optimierung in der Energiewirtschaft}, publisher = {VDI-Verlag, D{\"u}sseldorf}, pages = {105 -- 114}, year = {2011}, language = {en} } @misc{PfetschFuegenschuhGeissleretal., 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}, issn = {1438-0064}, doi = {10.1080/10556788.2014.888426}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-16531}, 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 mixed-integer non-convex nonlinear feasibility problem. The first phase consists of four distinct algorithms facilitating mixed-integer linear, mixed-integer nonlinear, reduced nonlinear, and complementarity constrained methods to compute possible settings for the discrete decisions. The second phase employs a precise continuous nonlinear programming model of the gas network. Using this setup, we are able to compute high quality solutions to real-world industrial instances whose size is significantly larger than networks that have appeared in the literature previously.}, language = {en} } @misc{MartinGeisslerHaynetal., author = {Martin, Alexander and Geißler, Bj{\"o}rn and Hayn, Christine and Hiller, Benjamin and Humpola, Jesco and Koch, Thorsten and Lehmann, Thomas and Morsi, Antonio and Pfetsch, Marc and Schewe, Lars and Schmidt, Martin and Schultz, R{\"u}diger and Schwarz, Robert and Schweiger, Jonas and Steinbach, Marc and Willert, Bernhard}, title = {Optimierung Technischer Kapazit{\"a}ten in Gasnetzen}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-15121}, abstract = {Die mittel- und l{\"a}ngerfristige Planung f{\"u}r den Gastransport hat sich durch {\"A}nderungen in den regulatorischen Rahmenbedingungen stark verkompliziert. Kernpunkt ist die Trennung von Gashandel und -transport. Dieser Artikel diskutiert die hieraus resultierenden mathematischen Planungsprobleme, welche als Validierung von Nominierungen und Buchungen, Bestimmung der technischen Kapazit{\"a}t und Topologieplanung bezeichnet werden. Diese mathematischen Optimierungsprobleme werden vorgestellt und L{\"o}sungsans{\"a}tze skizziert.}, language = {de} } @misc{Pfetsch, author = {Pfetsch, Marc}, title = {A Branch-And-Cut for the Maximum Feasible Subsystem Problem}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8797}, number = {05-46}, abstract = {We present a branch-and-cut algorithm for the NP-hard maximum feasible subsystem problem: For a given infeasible linear inequality system, determine a feasible subsystem containing as many inequalities as possible. The complementary problem, where one has to remove as few inequalities as possible in order to render the system feasible, can be formulated as a set covering problem. The rows of this formulation correspond to irreducible infeasible subsystems, which can be exponentially many. The main issue of a branch-and-cut algorithm for MaxFS is to efficiently find such infeasible subsystems. We present three heuristics for the corresponding NP-hard separation problem and discuss further cutting planes. This paper contains an extensive computational study of our implementation on a variety of instances arising in a number of applications.}, language = {en} } @misc{JoswigPfetsch, author = {Joswig, Michael and Pfetsch, Marc}, title = {Computing Optimal Morse Matchings}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8120}, number = {04-37}, abstract = {Morse matchings capture the essential structural information of discrete Morse functions. We show that computing optimal Morse matchings is NP-hard and give an integer programming formulation for the problem. Then we present polyhedral results for the corresponding polytope and report on computational results.}, language = {en} } @misc{BorndoerferGroetschelPfetsch, author = {Bornd{\"o}rfer, Ralf and Gr{\"o}tschel, Martin and Pfetsch, Marc}, title = {A Column-Generation Approach to Line Planning in Public Transport}, doi = {/10.1287/trsc.1060.0161}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8522}, number = {05-18}, abstract = {The line planning problem is one of the fundamental problems in strategic planning of public and rail transport. It consists in finding lines and corresponding frequencies in a transport network such that a given travel demand can be satisfied. There are (at least) two objectives. The transport company wishes to minimize operating costs, the passengers want to minimize travel times. We propose a n ew multi-commodity flow model for line planning. Its main features, in comparison to existing models, are that the passenger paths can be freely routed and that the lines are generated dynamically. We discuss properties of this model and investigate its complexity. Results with data for the city of Potsdam, Germany, are reported.}, language = {en} } @misc{BorndoerferNeumannPfetsch, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {Fare Planning for Public Transport}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8541}, number = {05-20}, abstract = {In this paper we introduce the fare planning problem for public transport which consists in designing a system of fares maximizing revenue. We propose a new simple general model for this problem. It i s based on a demand function and constraints for the different fares. The constraints define the structure of the fare system, e.g., distance dependent fares or zone fares. We discuss a simple example with a quadratic demand function and distance dependent fares. Then we introduce a more realistic discrete choice model in which passengers choose between different alternatives depending on the numb er of trips per month. We demonstrate the examples by computational experiments.}, language = {en} } @misc{BorndoerferGroetschelPfetsch, author = {Bornd{\"o}rfer, Ralf and Gr{\"o}tschel, Martin and Pfetsch, Marc}, title = {Public Transport to the fORe!}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8562}, number = {05-22}, abstract = {Can OR methods help the public transport industry to break even? The article gives evidence that there exist significant potentials in this direction, which can be harnessed by a combination of modern mathematical methods and local planning knowledge. Many of the planning steps in public transport are classical combinatorial problems, which can be solved in unprecedented size and quality due the rapid progress in large-scale optimization. Three examples on vehicle scheduling, duty scheduling, and integrated vehicle and duty scheduling illustrate the level that has been reached and the improvements that can be achieved today. Extensions of such methods to further questions of strategic, online, and market-oriented planning are currently investigated. In this way, OR can make a significant contribution to answer the basic but extremely difficult question ``What is a good public transport network?.}, language = {en} } @misc{BorndoerferGroetschelPfetsch, author = {Bornd{\"o}rfer, Ralf and Gr{\"o}tschel, Martin and Pfetsch, Marc}, title = {Models for Line Planning in Public Transport}, doi = {10.1007/978-3-540-73312-6_18}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-7854}, number = {04-10}, abstract = {The \emph{line planning problem} is one of the fundamental problems in strategic planning of public and rail transport. It consists of finding lines and corresponding frequencies in a public transport network such that a given travel demand can be satisfied. There are (at least) two objectives. The transport company wishes to minimize its operating cost; the passengers request short travel times. We propose two new multi-commodity flow models for line planning. Their main features, in comparison to existing models, are that the passenger paths can be freely routed and that the lines are generated dynamically.}, language = {en} } @misc{BorndoerferNeumannPfetsch, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {The Steiner Connectivity Problem}, issn = {1438-0064}, doi = {10.1007/s10107-012-0564-5}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11171}, number = {09-07}, abstract = {The Steiner connectivity problem is a generalization of the Steiner tree problem. It consists in finding a minimum cost set of simple paths to connect a subset of nodes in an undirected graph. We show that polyhedral and algorithmic results on the Steiner tree problem carry over to the Steiner connectivity problem, namely, the Steiner cut and the Steiner partition inequalities, as well as the associated polynomial time separation algorithms, can be generalized. Similar to the Steiner tree case, a directed formulation, which is stronger than the natural undirected one, plays a central role.}, language = {en} } @misc{BorndoerferNeumannPfetsch, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {Angebotsplanung im {\"o}ffentlichen Nahverkehr}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10555}, number = {08-04}, abstract = {Die Angebotsplanung im {\"o}ffentlichen Nahverkehr umfasst die Aufgaben der Netz-, Linien-,Fahr- und Preisplanung. Wir stellen zwei mathematische Optimierungsmodelle zur Linien- und Preisplanung vor. Wir zeigen anhand von Berechnungen f{\"u}r die Verkehrsbetriebe in Potsdam(ViP), dass sich damit komplexe Zusammenh{\"a}nge quantitativ analysieren lassen. Auf diese Weise untersuchen wir die Auswirkungen von Freiheitsgraden auf die Konstruktion von Linien und die Wahl von Reisewegen der Passagiere, Abh{\"a}ngigkeiten zwischen Kosten und Reisezeiten sowie den Einfluss verschiedener Preissysteme auf Nachfrage und Kostendeckung.}, language = {de} } @misc{BertholdHeinzPfetsch, author = {Berthold, Timo and Heinz, Stefan and Pfetsch, Marc}, title = {Nonlinear pseudo-Boolean optimization: relaxation or propagation?}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11232}, number = {09-11}, abstract = {Pseudo-Boolean problems lie on the border between satisfiability problems, constraint programming, and integer programming. In particular, nonlinear constraints in pseudo-Boolean optimization can be handled by methods arising in these different fields: One can either linearize them and work on a linear programming relaxation or one can treat them directly by propagation. In this paper, we investigate the individual strengths of these approaches and compare their computational performance. Furthermore, we integrate these techniques into a branch-and-cut-and-propagate framework, resulting in an efficient nonlinear pseudo-Boolean solver.}, language = {en} } @misc{BorndoerferNeumannPfetsch, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {The Line Connectivity Problem}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10820}, number = {08-31}, abstract = {This paper introduces the "line connectivity problem", a generalization of the Steiner tree problem and a special case of the line planning problem. We study its complexity and give an IP formulation in terms of an exponential number of constraints associated with "line cut constraints". These inequalities can be separated in polynomial time. We also generalize the Steiner partition inequalities.}, language = {en} } @misc{BertholdPfetsch, author = {Berthold, Timo and Pfetsch, Marc}, title = {Detecting Orbitopal Symmetries}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10842}, number = {08-33}, abstract = {Orbitopes can be used to handle symmetries which arise in integer programming formulations with an inherent assignment structure. We investigate the detection of symmetries appearing in this approach. We show that detecting so-called orbitopal symmetries is graph-isomorphism hard in general, but can be performed in linear time if the assignment structure is known.}, language = {en} } @misc{TorresTorresBorndoerferetal., author = {Torres, Luis Miguel and Torres, Ramiro and Bornd{\"o}rfer, Ralf and Pfetsch, Marc}, title = {Line Planning on Paths and Tree Networks with Applications to the Quito Trolebus System}, organization = {ZIB}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10869}, number = {08-35}, abstract = {Line planning is an important step in the strategic planning process of a public transportation system. In this paper, we discuss an optimization model for this problem in order to minimize operation costs while guaranteeing a certain level of quality of service, in terms of available transport capacity. We analyze the problem for path and tree network topologies as well as several categories of line operation that are important for the Quito Trolebus system. It turns out that, from a computational complexity worst case point of view, the problem is hard in all but the most simple variants. In practice, however, instances based on real data from the Trolebus System in Quito can be solved quite well, and significant optimization potentials can be demonstrated.}, language = {en} } @misc{TorresTorresBorndoerferetal., author = {Torres, Luis Miguel and Torres, Ramiro and Bornd{\"o}rfer, Ralf and Pfetsch, Marc}, title = {On the Line Planning Problem in Tree Networks}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11069}, number = {08-52}, abstract = {We introduce an optimization model for the line planning problem in a public transportation system that aims at minimizing operational costs while ensuring a given level of quality of service in terms of available transport capacity. We discuss the computational complexity of the model for tree network topologies and line structures that arise in a real-world application at the Trolebus Integrated System in Quito. Computational results for this system are reported.}, language = {en} } @misc{TorresTorresBorndoerferetal., author = {Torres, Luis Miguel and Torres, Ramiro and Bornd{\"o}rfer, Ralf and Pfetsch, Marc}, title = {Line Planning on Paths and Tree Networks with Applications to the Quito Trolebus System (Extended Abstract)}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-11076}, number = {08-53}, abstract = {Line planning is an important step in the strategic planning process of a public transportation system. In this paper, we discuss an optimization model for this problem in order to minimize operation costs while guaranteeing a certain level of quality of service, in terms of available transport capacity. We analyze the problem for path and tree network topologies as well as several categories of line operation that are important for the Quito Trolebus system. It turns out that, from a computational complexity worst case point of view, the problem is hard in all but the most simple variants. In practice, however, instances based on real data from the Trolebus System in Quito can be solved quite well, and significant optimization potentials can be demonstrated.}, language = {en} } @misc{BertholdHeinzPfetsch, author = {Berthold, Timo and Heinz, Stefan and Pfetsch, Marc}, title = {Solving Pseudo-Boolean Problems with SCIP}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10671}, number = {08-12}, abstract = {Pseudo-Boolean problems generalize SAT problems by allowing linear constraints and a linear objective function. Different solvers, mainly having their roots in the SAT domain, have been proposed and compared,for instance, in Pseudo-Boolean evaluations. One can also formulate Pseudo-Boolean models as integer programming models. That is,Pseudo-Boolean problems lie on the border between the SAT domain and the integer programming field. In this paper, we approach Pseudo-Boolean problems from the integer programming side. We introduce the framework SCIP that implements constraint integer programming techniques. It integrates methods from constraint programming, integer programming, and SAT-solving: the solution of linear programming relaxations, propagation of linear as well as nonlinear constraints, and conflict analysis. We argue that this approach is suitable for Pseudo-Boolean instances containing general linear constraints, while it is less efficient for pure SAT problems. We present extensive computational experiments on the test set used for the Pseudo-Boolean evaluation 2007. We show that our approach is very efficient for optimization instances and competitive for feasibility problems. For the nonlinear parts, we also investigate the influence of linear programming relaxations and propagation methods on the performance. It turns out that both techniques are helpful for obtaining an efficient solution method.}, language = {en} } @misc{BorndoerferNeumannPfetsch, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {Models for Fare Planning in Public Transport}, issn = {1438-0064}, doi = {10.1016/j.dam.2012.02.027}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10708}, number = {08-16}, abstract = {The optimization of fare systems in public transit allows to pursue objectives such as the maximization of demand, revenue, profit, or social welfare. We propose a non-linear optimization approach to fare planning that is based on a detailed discrete choice model of user behavior. The approach allows to analyze different fare structures, optimization objectives, and operational scenarios involving, e.g., subsidies. We use the resulting models to compute optimized fare systems for the city of Potsdam, Germany.}, language = {en} } @misc{HarksHeinzPfetsch, author = {Harks, Tobias and Heinz, Stefan and Pfetsch, Marc}, title = {Competitive Online Multicommodity Routing}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9212}, number = {06-27}, abstract = {We study online multicommodity minimum cost routing problems in networks, where commodities have to be routed sequentially. Arcs are equipped with load dependent price functions defining the routing weights. We discuss an online algorithm that routes each commodity by minimizing a convex cost function that depends on the demands that are previously routed. We present a competitive analysis of this algorithm showing that for affine linear price functions this algorithm is \$4K/2+K\$-competitive, where \$K\$ is the number of commodities. For the parallel arc case this algorithm is optimal. Without restrictions on the price functions and network, no algorithm is competitive. Finally, we investigate a variant in which the demands have to be routed unsplittably.}, language = {en} } @misc{HarksHeinzPfetsch, author = {Harks, Tobias and Heinz, Stefan and Pfetsch, Marc}, title = {Competitive Online Multicommodity Routing}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9599}, number = {07-16}, abstract = {In this paper we study online multicommodity routing problems in networks, in which commodities have to be routed sequentially. The flow of each commodity can be split on several paths. Arcs are equipped with load dependent price functions defining routing costs, which have to be minimized. We discuss a greedy online algorithm that routes each commodity by minimizing a convex cost function that only depends on the demands previously routed. We present a competitive analysis of this algorithm showing that for affine linear price functions this algorithm is 4K2 (1+K)2 -competitive, where K is the number of commodities. For the single-source single-destination case, this algorithm is optimal. Without restrictions on the price functions and network, no algorithm is competitive. Finally, we investigate a variant in which the demands have to be routed unsplittably.}, language = {en} } @misc{KaibelPeinhardtPfetsch, author = {Kaibel, Volker and Peinhardt, Matthias and Pfetsch, Marc}, title = {Orbitopal Fixing}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9422}, number = {06-48}, abstract = {The topic of this paper are integer programming models in which a subset of 0/1-variables encode a partitioning of a set of objects into disjoint subsets. Such models can be surprisingly hard to solve by branch-and-cut algorithms if the permutation of the subsets of the partition is irrelevant. This kind of symmetry unnecessarily blows up the branch-and-cut tree. We present a general tool, called orbitopal fixing, for enhancing the capabilities of branch-and-cut algorithms in solving this kind of symmetric integer programming models. We devise a linear time algorithm that, applied at each node of the branch-and-cut tree, removes redundant parts of the tree produced by the above mentioned permutations. The method relies on certain polyhedra, called orbitopes, which have been investigated in (Kaibel and Pfetsch (2006)). However, it does not add inequalities to the model, and thus, it does not increase the difficulty of solving the linear programming relaxations. We demonstrate the computational power of orbitopal fixing at the example of a graph partitioning problem motivated from frequency planning in mobile telecommunication networks.}, language = {en} } @misc{JokarPfetsch, author = {Jokar, Sadegh and Pfetsch, Marc}, title = {Exact and Approximate Sparse Solutions of Underdetermined Linear Equations}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9488}, number = {07-05}, abstract = {In this paper, we empirically investigate the NP-hard problem of finding sparse solutions to linear equation systems, i.e., solutions with as few nonzeros as possible. This problem has received considerable interest in the sparse approximation and signal processing literature, recently. We use a branch-and-cut approach via the maximum feasible subsystem problem to compute optimal solutions for small instances and investigate the uniqueness of the optimal solutions. We furthermore discuss five (modifications of) heuristics for this problem that appear in different parts of the literature. For small instances, the exact optimal solutions allow us to evaluate the quality of the heuristics, while for larger instances we compare their relative performance. One outcome is that the basis pursuit heuristic performs worse, compared to the other methods. Among the best heuristics are a method due to Mangasarian and a bilinear approach.}, language = {en} } @misc{KaibelPfetsch, author = {Kaibel, Volker and Pfetsch, Marc}, title = {Packing and Partitioning Orbitopes}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9104}, number = {06-17}, abstract = {We introduce orbitopes as the convex hulls of 0/1-matrices that are lexicographically maximal subject to a group acting on the columns. Special cases are packing and partitioning orbitopes, which arise from restrictions to matrices with at most or exactly one 1-entry in each row, respectively. The goal of investigating these polytopes is to gain insight into ways of breaking certain symmetries in integer programs by adding constraints, e.g., for a well-known formulation of the graph coloring problem. We provide a thorough polyhedral investigation of packing and partitioning orbitopes for the cases in which the group acting on the columns is the cyclic group or the symmetric group. Our main results are complete linear inequality descriptions of these polytopes by facet-defining inequalities. For the cyclic group case, the descriptions turn out to be totally unimodular, while for the symmetric group case, both the description and the proof are more involved. The associated separation problems can be solved in linear time.}, language = {en} } @misc{BorndoerferNeumannPfetsch, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {Optimal Fares for Public Transport}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8698}, number = {05-35}, abstract = {The \emph{fare planning problem} for public transport is to design a system of fares that maximize the revenue. We introduce a nonlinear optimization model to approach this problem. It is based on a d iscrete choice logit model that expresses demand as a function of the fares. We illustrate our approach by computing and comparing two different fare systems for the intercity network of the Netherlands.}, language = {en} } @misc{PfetschBorndoerfer, author = {Pfetsch, Marc and Bornd{\"o}rfer, Ralf}, title = {Routing in Line Planning for Public Transportation}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-8706}, number = {05-36}, abstract = {The line planning problem is one of the fundamental problems in strategic planning of public and rail transport. It consists in finding lines and corresponding frequencies in a network such that a giv en demand can be satisfied. There are two objectives. Passengers want to minimize travel times, the transport company wishes to minimize operating costs. We investigate three variants of a multi-commo dity flow model for line planning that differ with respect to passenger routings. The first model allows arbitrary routings, the second only unsplittable routings, and the third only shortest path rou tings with respect to the network. We compare these models theoretically and computationally on data for the city of Potsdam.}, language = {en} } @misc{HarksHeinzPfetschetal., author = {Harks, Tobias and Heinz, Stefan and Pfetsch, Marc and Vredeveld, Tjark}, title = {Online Multicommodity Routing with Time Windows}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9654}, number = {07-22}, abstract = {We consider a multicommodity routing problem, where demands are released \emph{online} and have to be routed in a network during specified time windows. The objective is to minimize a time and load dependent convex cost function of the aggregate arc flow. First, we study the fractional routing variant. We present two online algorithms, called Seq and Seq\$^2\$. Our first main result states that, for cost functions defined by polynomial price functions with nonnegative coefficients and maximum degree~\$d\$, the competitive ratio of Seq and Seq\$^2\$ is at most \$(d+1)^{d+1}\$, which is tight. We also present lower bounds of \$(0.265\,(d+1))^{d+1}\$ for any online algorithm. In the case of a network with two nodes and parallel arcs, we prove a lower bound of \$(2-\frac{1}{2} \sqrt{3})\$ on the competitive ratio for Seq and Seq\$^2\$, even for affine linear price functions. Furthermore, we study resource augmentation, where the online algorithm has to route less demand than the offline adversary. Second, we consider unsplittable routings. For this setting, we present two online algorithms, called U-Seq and U-Seq\$^2\$. We prove that for polynomial price functions with nonnegative coefficients and maximum degree~\$d\$, the competitive ratio of U-Seq and U-Seq\$^2\$ is bounded by \$O{1.77^d\,d^{d+1}}\$. We present lower bounds of \$(0.5307\,(d+1))^{d+1}\$ for any online algorithm and \$(d+1)^{d+1}\$ for our algorithms. Third, we consider a special case of our framework: online load balancing in the \$\ell_p\$-norm. For the fractional and unsplittable variant of this problem, we show that our online algorithms are \$p\$ and \$O{p}\$ competitive, respectively. Such results where previously known only for scheduling jobs on restricted (un)related parallel machines.}, language = {en} } @misc{BertholdHeinzPfetschetal., author = {Berthold, Timo and Heinz, Stefan and Pfetsch, Marc and Vigerske, Stefan}, title = {Large Neighborhood Search beyond MIP}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-12989}, number = {11-21}, abstract = {Large neighborhood search (LNS) heuristics are an important component of modern branch-and-cut algorithms for solving mixed-integer linear programs (MIPs). Most of these LNS heuristics use the LP relaxation as the basis for their search, which is a reasonable choice in case of MIPs. However, for more general problem classes, the LP relaxation alone may not contain enough information about the original problem to find feasible solutions with these heuristics, e.g., if the problem is nonlinear or not all constraints are present in the current relaxation. In this paper, we discuss a generic way to extend LNS heuristics that have been developed for MIP to constraint integer programming (CIP), which is a generalization of MIP in the direction of constraint programming (CP). We present computational results of LNS heuristics for three problem classes: mixed-integer quadratically constrained programs, nonlinear pseudo-Boolean optimization instances, and resource-constrained project scheduling problems. Therefore, we have implemented extended versions of the following LNS heuristics in the constraint integer programming framework SCIP: Local Branching, RINS, RENS, Crossover, and DINS. Our results indicate that a generic generalization of LNS heuristics to CIP considerably improves the success rate of these heuristics.}, language = {en} } @article{BorndoerferGroetschelPfetsch2007, author = {Bornd{\"o}rfer, Ralf and Gr{\"o}tschel, Martin and Pfetsch, Marc}, title = {A Column-Generation Approach to Line Planning in Public Transport}, series = {Transportation Science (INFORMS)}, volume = {41}, journal = {Transportation Science (INFORMS)}, number = {1}, doi = {10.1287/trsc.1060.0161}, pages = {123 -- 132}, year = {2007}, language = {en} } @misc{KochMartinPfetsch, author = {Koch, Thorsten and Martin, Alexander and Pfetsch, Marc}, title = {Progress in Academic Computational Integer Programming}, series = {Facets of Combinatorial Optimization}, journal = {Facets of Combinatorial Optimization}, editor = {J{\"u}nger, Michael and Reinelt, Gerhard}, publisher = {Springer}, doi = {10.1007/978-3-642-38189-8_19}, pages = {483 -- 506}, language = {en} } @book{KochHillerPfetschetal., author = {Koch, Thorsten and Hiller, Benjamin and Pfetsch, Marc and Schewe, Lars}, title = {Evaluating Gas Network Capacities}, publisher = {SIAM}, isbn = {978-1-611973-68-6}, pages = {xvi + 376 pages}, language = {en} } @article{HumpolaJoormannOucherifetal., author = {Humpola, Jesco and Joormann, Imke and Oucherif, Djamal and Pfetsch, Marc and Schewe, Lars and Schmidt, Martin and Schwarz, Robert}, title = {GasLib - A Library of Gas Network Instances}, series = {Optimization Online}, journal = {Optimization Online}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-57950}, abstract = {The development of mathematical simulation and optimization models and algorithms for solving gas transport problems is an active field of research. In order to test and compare these models and algorithms, gas network instances together with demand data are needed. The goal of GasLib is to provide a set of publicly available gas network instances that can be used by researchers in the field of gas transport. The advantages are that researchers save time by using these instances and that different models and algorithms can be compared on the same specified test sets. The library instances are encoded in an XML format. In this paper, we explain this format and present the instances that are available in the library.}, language = {en} } @inproceedings{BertholdHeinzPfetschetal., author = {Berthold, Timo and Heinz, Stefan and Pfetsch, Marc and Vigerske, Stefan}, title = {Large Neighborhood Search beyond MIP}, series = {Proceedings of the 9th Metaheuristics International Conference (MIC 2011)}, booktitle = {Proceedings of the 9th Metaheuristics International Conference (MIC 2011)}, isbn = {978-88-900984-3-7}, pages = {51 -- 60}, abstract = {Large neighborhood search (LNS) heuristics are an important component of modern branch-and-cut algorithms for solving mixed-integer linear programs (MIPs). Most of these LNS heuristics use the LP relaxation as the basis for their search, which is a reasonable choice in case of MIPs. However, for more general problem classes, the LP relaxation alone may not contain enough information about the original problem to find feasible solutions with these heuristics, e.g., if the problem is nonlinear or not all constraints are present in the current relaxation. In this paper, we discuss a generic way to extend LNS heuristics that have been developed for MIP to constraint integer programming (CIP), which is a generalization of MIP in the direction of constraint programming (CP). We present computational results of LNS heuristics for three problem classes: mixed-integer quadratically constrained programs, nonlinear pseudo-Boolean optimization instances, and resource-constrained project scheduling problems. Therefore, we have implemented extended versions of the following LNS heuristics in the constraint integer programming framework SCIP: Local Branching, RINS, RENS, Crossover, and DINS. Our results indicate that a generic generalization of LNS heuristics to CIP considerably improves the success rate of these heuristics.}, language = {en} } @article{BorndoerferKarbsteinPfetsch, author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Pfetsch, Marc}, title = {The Steiner connectivity problem}, series = {Mathematical Programming A}, volume = {142}, journal = {Mathematical Programming A}, number = {1}, doi = {10.1007/s10107-012-0564-5}, pages = {133 -- 167}, language = {en} } @article{BorndoerferKarbsteinPfetsch, author = {Bornd{\"o}rfer, Ralf and Karbstein, Marika and Pfetsch, Marc}, title = {Models for Fare Planning in Public Transport}, series = {Discrete Applied Mathematics}, volume = {160}, journal = {Discrete Applied Mathematics}, number = {18}, doi = {10.1016/j.dam.2012.02.027}, pages = {2591 -- 2605}, language = {en} } @article{SchmidtAssmannBurlacuetal., author = {Schmidt, Martin and Assmann, Denis and Burlacu, Robert and Humpola, Jesco and Joormann, Imke and Kanelakis, Nikolaos and Koch, Thorsten and Oucherif, Djamal and Pfetsch, Marc and Schewe, Lars and Schwarz, Robert and Sirvent, Matthias}, title = {GasLib - A Library of Gas Network Instances}, series = {Data}, volume = {2}, journal = {Data}, number = {4}, doi = {10.3390/data2040040}, language = {en} } @incollection{BorndoerferNeumannPfetsch2006, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {Optimal Fares for Public Transport}, series = {Operations Research Proceedings 2005}, booktitle = {Operations Research Proceedings 2005}, editor = {Haasis, Hans-Dietrich and Kopfer, Herbert and Sch{\"o}nberger, J{\"o}rn}, publisher = {Springer-Verlag}, pages = {29 -- 36}, year = {2006}, language = {en} } @inproceedings{BorndoerferNeumannPfetsch2009, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {Line Planning and Connectivity}, series = {Models and Algorithms for Optimization in Logistics}, booktitle = {Models and Algorithms for Optimization in Logistics}, number = {09261}, editor = {Barnhart, Cynthia and Clausen, Uwe and Lauther, Ulrich and M{\"o}hring, Rolf}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany}, address = {Dagstuhl, Germany}, year = {2009}, language = {en} } @inproceedings{BorndoerferGroetschelPfetsch2008, author = {Bornd{\"o}rfer, Ralf and Gr{\"o}tschel, Martin and Pfetsch, Marc}, title = {Models for Line Planning in Public Transport}, series = {Computer-aided Systems in Public Transport (CASPT 2004)}, volume = {600}, booktitle = {Computer-aided Systems in Public Transport (CASPT 2004)}, editor = {Hickman, Mark and Mirchandani, Pitu and Voß, Stefan}, publisher = {Springer-Verlag}, doi = {10.1007/978-3-540-73312-6_18}, pages = {363 -- 378}, year = {2008}, language = {en} } @inproceedings{BorndoerferNeumannPfetsch2008, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {Angebotsplanung im {\"o}ffentlichen Nahverkehr}, series = {HEUREKA'08}, booktitle = {HEUREKA'08}, publisher = {FGSV Verlag}, year = {2008}, language = {en} } @inproceedings{TorresTorresBorndoerferetal.2008, author = {Torres, Luis Miguel and Torres, Ramiro and Bornd{\"o}rfer, Ralf and Pfetsch, Marc}, title = {Line Planning on Paths and Tree Networks with Applications to the Quito Trolebus System}, series = {ATMOS 2008 - 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems}, booktitle = {ATMOS 2008 - 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems}, editor = {Fischetti, Matteo and Widmayer, Peter}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany}, address = {Dagstuhl, Germany}, year = {2008}, language = {en} } @inproceedings{BorndoerferNeumannPfetsch2009, author = {Bornd{\"o}rfer, Ralf and Neumann, Marika and Pfetsch, Marc}, title = {The Line Connectivity Problem}, series = {Operations Research Proceedings 2008}, booktitle = {Operations Research Proceedings 2008}, editor = {Fleischmann, Bernhard and Borgwardt, Karl and Klein, Robert and Tuma, Axel}, publisher = {Springer-Verlag}, pages = {557 -- 562}, year = {2009}, language = {en} } @article{BorndoerferGroetschelPfetsch2006, author = {Bornd{\"o}rfer, Ralf and Gr{\"o}tschel, Martin and Pfetsch, Marc}, title = {Public transport to the fORe}, series = {OR/MS Today}, journal = {OR/MS Today}, pages = {30 -- 40}, year = {2006}, language = {en} } @inproceedings{PfetschBorndoerfer2006, author = {Pfetsch, Marc and Bornd{\"o}rfer, Ralf}, title = {Routing in Line Planning for Public Transportation}, series = {Operations Research Proceedings 2005}, booktitle = {Operations Research Proceedings 2005}, editor = {Haasis, Hans-Dietrich}, publisher = {Springer-Verlag}, pages = {405 -- 410}, year = {2006}, language = {en} } @inproceedings{BertholdHeinzPfetsch2009, author = {Berthold, Timo and Heinz, Stefan and Pfetsch, Marc}, title = {Nonlinear pseudo-Boolean optimization}, series = {Theory and Applications of Satisfiability Testing - SAT 2009}, volume = {5584}, booktitle = {Theory and Applications of Satisfiability Testing - SAT 2009}, editor = {Kullmann, Oliver}, publisher = {Springer}, pages = {441 -- 446}, year = {2009}, language = {en} } @inproceedings{BertholdPfetsch2009, author = {Berthold, Timo and Pfetsch, Marc}, title = {Detecting Orbitopal Symmetries}, series = {Operations Research Proceedings 2008}, booktitle = {Operations Research Proceedings 2008}, editor = {Fleischmann, Bernhard and Borgwardt, Karl and Klein, Robert and Tuma, Axel}, publisher = {Springer-Verlag}, pages = {433 -- 438}, year = {2009}, language = {en} } @incollection{KochPfetschRoevekamp, author = {Koch, Thorsten and Pfetsch, Marc and R{\"o}vekamp, Jessica}, title = {Introduction}, series = {Evaluating Gas Network Capacities}, booktitle = {Evaluating Gas Network Capacities}, publisher = {Society for Industrial and Applied Mathematics}, isbn = {9781611973686}, pages = {3 -- 16}, language = {en} } @incollection{BargmannEbbersHeineckeetal., author = {Bargmann, Dagmar and Ebbers, Mirko and Heinecke, Nina and Koch, Thorsten and K{\"u}hl, Veronika and Pelzer, Antje and Pfetsch, Marc and R{\"o}vekamp, Jessica and Spreckelsen, Klaus}, title = {State-of-the-art in evaluating gas network capacities}, series = {Evaluating Gas Network Capacities}, booktitle = {Evaluating Gas Network Capacities}, publisher = {Society for Industrial and Applied Mathematics}, isbn = {9781611973686}, pages = {65 -- 84}, language = {en} } @incollection{ScheweKochMartinetal., author = {Schewe, Lars and Koch, Thorsten and Martin, Alexander and Pfetsch, Marc}, title = {Mathematical optimization for evaluating gas network capacities}, series = {Evaluating Gas Network Capacities}, booktitle = {Evaluating Gas Network Capacities}, publisher = {Society for Industrial and Applied Mathematics}, isbn = {9781611973686}, pages = {87 -- 102}, language = {en} } @incollection{HillerHumpolaLehmannetal., author = {Hiller, Benjamin and Humpola, Jesco and Lehmann, Thomas and Lenz, Ralf and Morsi, Antonio and Pfetsch, Marc and Schewe, Lars and Schmidt, Martin and Schwarz, Robert and Schweiger, Jonas and Stangl, Claudia and Willert, Bernhard}, title = {Computational results for validation of nominations}, series = {Evaluating Gas Network Capacities}, volume = {SIAM-MOS series on Optimization}, booktitle = {Evaluating Gas Network Capacities}, isbn = {9781611973686}, abstract = {The different approaches to solve the validation of nomination problem presented in the previous chapters are evaluated computationally in this chapter. Each approach is analyzed individually, as well as the complete solvers for these problems. We demonstrate that the presented approaches can successfully solve large-scale real-world instances.}, language = {en} } @misc{HendelAndersonLeBodicetal., author = {Hendel, Gregor and Anderson, Daniel and Le Bodic, Pierre and Pfetsch, Marc}, title = {Estimating the Size of Branch-And-Bound Trees}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-78144}, abstract = {This paper investigates the estimation of the size of Branch-and-Bound (B\&B) trees for solving mixed-integer programs. We first prove that the size of the B\&B tree cannot be approximated within a factor of~2 for general binary programs, unless P equals NP. Second, we review measures of the progress of the B\&B search, such as the gap, and propose a new measure, which we call leaf frequency. We study two simple ways to transform these progress measures into B\&B tree size estimates, either as a direct projection, or via double-exponential smoothing, a standard time-series forecasting technique. We then combine different progress measures and their trends into nontrivial estimates using Machine Learning techniques, which yields more precise estimates than any individual measure. The best method we have identified uses all individual measures as features of a random forest model. In a large computational study, we train and validate all methods on the publicly available MIPLIB and Coral general purpose benchmark sets. On average, the best method estimates B\&B tree sizes within a factor of 3 on the set of unseen test instances even during the early stage of the search, and improves in accuracy as the search progresses. It also achieves a factor 2 over the entire search on each out of six additional sets of homogeneous instances we have tested. All techniques are available in version 7 of the branch-and-cut framework SCIP.}, language = {en} } @inproceedings{PfetschPokutta, author = {Pfetsch, Marc and Pokutta, Sebastian}, title = {IPBoost - Non-Convex Boosting via Integer Programming}, series = {Proceedings of ICML}, booktitle = {Proceedings of ICML}, language = {en} } @article{Le BodicPfetschPavelkaetal., author = {Le Bodic, P. and Pfetsch, Marc and Pavelka, J. and Pokutta, Sebastian}, title = {Solving MIPs via Scaling-based Augmentation}, series = {Discrete Optimization}, volume = {27}, journal = {Discrete Optimization}, pages = {1 -- 25}, language = {en} } @article{KochSchmidtHilleretal., 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}, series = {German Success Stories in Industrial Mathematics}, 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}, language = {en} } @article{HendelAndersonLeBodicetal., author = {Hendel, Gregor and Anderson, Daniel and Le Bodic, Pierre and Pfetsch, Marc}, title = {Estimating the Size of Branch-And-Bound Trees}, series = {INFORMS Journal on Computing}, journal = {INFORMS Journal on Computing}, doi = {10.1287/ijoc.2021.1103}, abstract = {This paper investigates the estimation of the size of Branch-and-Bound (B\&B) trees for solving mixed-integer programs. We first prove that the size of the B\&B tree cannot be approximated within a factor of~2 for general binary programs, unless P equals NP. Second, we review measures of the progress of the B\&B search, such as the gap, and propose a new measure, which we call leaf frequency. We study two simple ways to transform these progress measures into B\&B tree size estimates, either as a direct projection, or via double-exponential smoothing, a standard time-series forecasting technique. We then combine different progress measures and their trends into nontrivial estimates using Machine Learning techniques, which yields more precise estimates than any individual measure. The best method we have identified uses all individual measures as features of a random forest model. In a large computational study, we train and validate all methods on the publicly available MIPLIB and Coral general purpose benchmark sets. On average, the best method estimates B\&B tree sizes within a factor of 3 on the set of unseen test instances even during the early stage of the search, and improves in accuracy as the search progresses. It also achieves a factor 2 over the entire search on each out of six additional sets of homogeneous instances we have tested. All techniques are available in version 7 of the branch-and-cut framework SCIP.}, language = {en} } @misc{MaherFischerGallyetal., author = {Maher, Stephen J. and Fischer, Tobias and Gally, Tristan and Gamrath, Gerald and Gleixner, Ambros and Gottwald, Robert Lion and Hendel, Gregor and Koch, Thorsten and L{\"u}bbecke, Marco and Miltenberger, Matthias and M{\"u}ller, Benjamin and Pfetsch, Marc and Puchert, Christian and Rehfeldt, Daniel and Schenker, Sebastian and Schwarz, Robert and Serrano, Felipe and Shinano, Yuji and Weninger, Dieter and Witt, Jonas T. and Witzig, Jakob}, title = {The SCIP Optimization Suite 4.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-62170}, abstract = {The SCIP Optimization Suite is a powerful collection of optimization software that consists of the branch-cut-and-price framework and mixed-integer programming solver SCIP, the linear programming solver SoPlex, the modeling language Zimpl, the parallelization framework UG, and the generic branch-cut-and-price solver GCG. Additionally, it features the extensions SCIP-Jack for solving Steiner tree problems, PolySCIP for solving multi-objective problems, and SCIP-SDP for solving mixed-integer semidefinite programs. The SCIP Optimization Suite has been continuously developed and has now reached version 4.0. The goal of this report is to present the recent changes to the collection. We not only describe the theoretical basis, but focus on implementation aspects and their computational consequences.}, language = {en} } @misc{GamrathFischerGallyetal., author = {Gamrath, Gerald and Fischer, Tobias and Gally, Tristan and Gleixner, Ambros and Hendel, Gregor and Koch, Thorsten and Maher, Stephen J. and Miltenberger, Matthias and M{\"u}ller, Benjamin and Pfetsch, Marc and Puchert, Christian and Rehfeldt, Daniel and Schenker, Sebastian and Schwarz, Robert and Serrano, Felipe and Shinano, Yuji and Vigerske, Stefan and Weninger, Dieter and Winkler, Michael and Witt, Jonas T. and Witzig, Jakob}, title = {The SCIP Optimization Suite 3.2}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-57675}, abstract = {The SCIP Optimization Suite is a software toolbox for generating and solving various classes of mathematical optimization problems. Its major components are the modeling language ZIMPL, the linear programming solver SoPlex, the constraint integer programming framework and mixed-integer linear and nonlinear programming solver SCIP, the UG framework for parallelization of branch-and-bound-based solvers, and the generic branch-cut-and-price solver GCG. It has been used in many applications from both academia and industry and is one of the leading non-commercial solvers. This paper highlights the new features of version 3.2 of the SCIP Optimization Suite. Version 3.2 was released in July 2015. This release comes with new presolving steps, primal heuristics, and branching rules within SCIP. In addition, version 3.2 includes a reoptimization feature and improved handling of quadratic constraints and special ordered sets. SoPlex can now solve LPs exactly over the rational number and performance improvements have been achieved by exploiting sparsity in more situations. UG has been tested successfully on 80,000 cores. A major new feature of UG is the functionality to parallelize a customized SCIP solver. GCG has been enhanced with a new separator, new primal heuristics, and improved column management. Finally, new and improved extensions of SCIP are presented, namely solvers for multi-criteria optimization, Steiner tree problems, and mixed-integer semidefinite programs.}, language = {en} } @misc{BestuzhevaBesanconChenetal., author = {Bestuzheva, Ksenia and Besan{\c{c}}on, Mathieu and Chen, Wei-Kun and Chmiela, Antonia and Donkiewicz, Tim and van Doornmalen, Jasper and Eifler, Leon and Gaul, Oliver and Gamrath, Gerald and Gleixner, Ambros and Gottwald, Leona and Graczyk, Christoph and Halbig, Katrin and Hoen, Alexander and Hojny, Christopher and van der Hulst, Rolf and Koch, Thorsten and L{\"u}bbecke, Marco and Maher, Stephen J. and Matter, Frederic and M{\"u}hmer, Erik and M{\"u}ller, Benjamin and Pfetsch, Marc E. and Rehfeldt, Daniel and Schlein, Steffan and Schl{\"o}sser, Franziska and Serrano, Felipe and Shinano, Yuji and Sofranac, Boro and Turner, Mark and Vigerske, Stefan and Wegscheider, Fabian and Wellner, Philipp and Weninger, Dieter and Witzig, Jakob}, title = {The SCIP Optimization Suite 8.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-85309}, 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 8.0 of the SCIP Optimization Suite. Major updates in SCIP include improvements in symmetry handling and decomposition algorithms, new cutting planes, a new plugin type for cut selection, and a complete rework of the way nonlinear constraints are handled. Additionally, SCIP 8.0 now supports interfaces for Julia as well as Matlab. Further, UG now includes a unified framework to parallelize all solvers, a utility to analyze computational experiments has been added to GCG, dual solutions can be postsolved by PaPILO, new heuristics and presolving methods were added to SCIP-SDP, and additional problem classes and major performance improvements are available in SCIP-Jack.}, language = {en} } @misc{GamrathAndersonBestuzhevaetal., author = {Gamrath, Gerald and Anderson, Daniel and Bestuzheva, Ksenia and Chen, Wei-Kun and Eifler, Leon and Gasse, Maxime and Gemander, Patrick and Gleixner, Ambros and Gottwald, Leona and Halbig, Katrin and Hendel, Gregor and Hojny, Christopher and Koch, Thorsten and Le Bodic, Pierre and Maher, Stephen J. and Matter, Frederic and Miltenberger, Matthias and M{\"u}hmer, Erik and M{\"u}ller, Benjamin and Pfetsch, Marc and Schl{\"o}sser, Franziska and Serrano, Felipe and Shinano, Yuji and Tawfik, Christine and Vigerske, Stefan and Wegscheider, Fabian and Weninger, Dieter and Witzig, Jakob}, title = {The SCIP Optimization Suite 7.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-78023}, abstract = {The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming frame- work SCIP. This paper discusses enhancements and extensions contained in version 7.0 of the SCIP Optimization Suite. The new version features the parallel presolving library PaPILO as a new addition to the suite. PaPILO 1.0 simplifies mixed-integer linear op- timization problems and can be used stand-alone or integrated into SCIP via a presolver plugin. SCIP 7.0 provides additional support for decomposition algorithms. Besides im- provements in the Benders' decomposition solver of SCIP, user-defined decomposition structures can be read, which are used by the automated Benders' decomposition solver and two primal heuristics. Additionally, SCIP 7.0 comes with a tree size estimation that is used to predict the completion of the overall solving process and potentially trigger restarts. Moreover, substantial performance improvements of the MIP core were achieved by new developments in presolving, primal heuristics, branching rules, conflict analysis, and symmetry handling. Last, not least, the report presents updates to other components and extensions of the SCIP Optimization Suite, in particular, the LP solver SoPlex and the mixed-integer semidefinite programming solver SCIP-SDP.}, language = {en} } @misc{GleixnerEiflerGallyetal., author = {Gleixner, Ambros and Eifler, Leon and Gally, Tristan and Gamrath, Gerald and Gemander, Patrick and Gottwald, Robert Lion and Hendel, Gregor and Hojny, Christopher and Koch, Thorsten and Miltenberger, Matthias and M{\"u}ller, Benjamin and Pfetsch, Marc and Puchert, Christian and Rehfeldt, Daniel and Schl{\"o}sser, Franziska and Serrano, Felipe and Shinano, Yuji and Viernickel, Jan Merlin and Vigerske, Stefan and Weninger, Dieter and Witt, Jonas T. and Witzig, Jakob}, title = {The SCIP Optimization Suite 5.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-66297}, abstract = {This article describes new features and enhanced algorithms made available in version 5.0 of the SCIP Optimization Suite. In its central component, the constraint integer programming solver SCIP, remarkable performance improvements have been achieved for solving mixed-integer linear and nonlinear programs. On MIPs, SCIP 5.0 is about 41 \% faster than SCIP 4.0 and over twice as fast on instances that take at least 100 seconds to solve. For MINLP, SCIP 5.0 is about 17 \% faster overall and 23 \% faster on instances that take at least 100 seconds to solve. This boost is due to algorithmic advances in several parts of the solver such as cutting plane generation and management, a new adaptive coordination of large neighborhood search heuristics, symmetry handling, and strengthened McCormick relaxations for bilinear terms in MINLPs. Besides discussing the theoretical background and the implementational aspects of these developments, the report describes recent additions for the other software packages connected to SCIP, in particular for the LP solver SoPlex, the Steiner tree solver SCIP-Jack, the MISDP solver SCIP-SDP, and the parallelization framework UG.}, language = {en} } @misc{GleixnerBastubbeEifleretal., 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}, 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} } @article{BestuzhevaBesanconChenetal., author = {Bestuzheva, Ksenia and Besan{\c{c}}on, Mathieu and Chen, Wei-Kun and Chmiela, Antonia and Donkiewicz, Tim and Doornmalen, Jasper and Eifler, Leon and Gaul, Oliver and Gamrath, Gerald and Gleixner, Ambros and Gottwald, Leona and Graczyk, Christoph and Halbig, Katrin and Hoen, Alexander and Hojny, Christopher and Hulst, Rolf and Koch, Thorsten and L{\"u}bbecke, Marco and Maher, Stephen J. and Matter, Frederic and M{\"u}hmer, Erik and M{\"u}ller, Benjamin and Pfetsch, Marc and Rehfeldt, Daniel and Schlein, Steffan and Schl{\"o}sser, Franziska and Serrano, Felipe and Shinano, Yuji and Sofranac, Boro and Turner, Mark and Vigerske, Stefan and Wegscheider, Fabian and Wellner, Philipp and Weninger, Dieter and Witzig, Jakob}, title = {Enabling research through the SCIP optimization suite 8.0}, series = {ACM Transactions on Mathematical Software}, volume = {49}, journal = {ACM Transactions on Mathematical Software}, number = {2}, doi = {10.1145/3585516}, pages = {1 -- 21}, abstract = {The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this article is on the role of the SCIP Optimization Suite in supporting research. SCIP's main design principles are discussed, followed by a presentation of the latest performance improvements and developments in version 8.0, which serve both as examples of SCIP's application as a research tool and as a platform for further developments. Furthermore, this article gives an overview of interfaces to other programming and modeling languages, new features that expand the possibilities for user interaction with the framework, and the latest developments in several extensions built upon SCIP.}, language = {en} } @inproceedings{ThuerckSofranacPfetschetal., author = {Thuerck, Daniel and Sofranac, Boro and Pfetsch, Marc and Pokutta, Sebastian}, title = {Learning cuts via enumeration oracles}, series = {Proceedings of Conference on Neural Information Processing Systems}, booktitle = {Proceedings of Conference on Neural Information Processing Systems}, language = {en} } @misc{BolusaniBesanconBestuzhevaetal., author = {Bolusani, Suresh and Besan{\c{c}}on, Mathieu and Bestuzheva, Ksenia and Chmiela, Antonia and Dion{\´i}sio, Jo{\~a}o and Donkiewicz, Tim and van Doornmalen, Jasper and Eifler, Leon and Ghannam, Mohammed and Gleixner, Ambros and Graczyk, Christoph and Halbig, Katrin and Hedtke, Ivo and Hoen, Alexander and Hojny, Christopher and van der Hulst, Rolf and Kamp, Dominik and Koch, Thorsten and Kofler, Kevin and Lentz, Jurgen and Manns, Julian and Mexi, Gioni and M{\"u}hmer, Erik and E. Pfetsch, Marc and Schl{\"o}sser, Franziska and Serrano, Felipe and Shinano, Yuji and Turner, Mark and Vigerske, Stefan and Weninger, Dieter and Xu, Liding}, title = {The SCIP Optimization Suite 9.0}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-95528}, abstract = {The SCIP Optimization Suite provides a collection of software packages for mathematical optimization, centered around the constraint integer programming framework SCIP. This report discusses the enhancements and extensions included in the SCIP Optimization Suite 9.0. The updates in SCIP 9.0 include improved symmetry handling, additions and improvements of nonlinear handlers and primal heuristics, a new cut generator and two new cut selection schemes, a new branching rule, a new LP interface, and several bug fixes. The SCIP Optimization Suite 9.0 also features new Rust and C++ interfaces for SCIP, new Python interface for SoPlex, along with enhancements to existing interfaces. The SCIP Optimization Suite 9.0 also includes new and improved features in the LP solver SoPlex, the presolving library PaPILO, the parallel framework UG, the decomposition framework GCG, and the SCIP extension SCIP-SDP. These additions and enhancements have resulted in an overall performance improvement of SCIP in terms of solving time, number of nodes in the branch-and-bound tree, as well as the reliability of the solver.}, language = {en} }