TY - CHAP A1 - Gamrath, Gerald A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Winkler, Michael T1 - Structure-Based Primal Heuristics for Mixed Integer Programming T2 - Optimization in the Real World N2 - Primal heuristics play an important role in the solving of mixed integer programs (MIPs). They help to reach optimality faster and provide good feasible solutions early in the solving process. In this paper, we present two new primal heuristics which take into account global structures available within MIP solvers to construct feasible solutions at the beginning of the solving process. These heuristics follow a large neighborhood search (LNS) approach and use global structures to define a neighborhood that is with high probability significantly easier to process while (hopefully) still containing good feasible solutions. The definition of the neighborhood is done by iteratively fixing variables and propagating these fixings. Thereby, fixings are determined based on the predicted impact they have on the subsequent domain propagation. The neighborhood is solved as a sub-MIP and solutions are transferred back to the original problem. Our computational experiments on standard MIP test sets show that the proposed heuristics find solutions for about every third instance and therewith help to improve the average solving time. Y1 - 2015 SN - 978-4-431-55419-6 U6 - https://doi.org/10.1007/978-4-431-55420-2_3 VL - 13 SP - 37 EP - 53 PB - Springer Japan ER - TY - GEN A1 - Witzig, Jakob A1 - Berthold, Timo A1 - Heinz, Stefan T1 - Experiments with Conflict Analysis in Mixed Integer Programming N2 - The analysis of infeasible subproblems plays an import role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally different concepts to generate valid global constraints from infeasible subproblems. The first is to analyze the sequence of implications obtained by domain propagation that led to infeasibility. The result of the analysis is one or more sets of contradicting variable bounds from which so-called conflict constraints can be generated. This concept has its origin in solving satisfiability problems and is similarly used in constraint programming. The second concept is to analyze infeasible linear programming (LP) relaxations. The dual LP solution provides a set of multipliers that can be used to generate a single new globally valid linear constraint. The main contribution of this short paper is an empirical evaluation of two ways to combine both approaches. Experiments are carried out on general MIP instances from standard public test sets such as Miplib2010; the presented algorithms have been implemented within the non-commercial MIP solver SCIP. Moreover, we present a pool-based approach to manage conflicts which addresses the way a MIP solver traverses the search tree better than aging strategies known from SAT solving. T3 - ZIB-Report - 16-63 Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-61087 SN - 1438-0064 ER - TY - JOUR A1 - Gessat, Michael A1 - Zachow, Stefan A1 - Burgert, Oliver A1 - Lemke, Heinz T1 - Geometric Meshes in Medical Applications - Steps towards a specification of Geometric Models in DICOM JF - Int. J. of Computer Assisted Radiology and Surgery (CARS) Y1 - 2007 U6 - https://doi.org/10.1007/s11548-007-0112-6 SP - 440 EP - 442 ER - TY - CHAP A1 - Krämer, Martin A1 - Herrmann, Karl-Heinz A1 - Boeth, Heide A1 - Tycowicz, Christoph von A1 - König, Christian A1 - Zachow, Stefan A1 - Ehrig, Rainald A1 - Hege, Hans-Christian A1 - Duda, Georg A1 - Reichenbach, Jürgen T1 - Measuring 3D knee dynamics using center out radial ultra-short echo time trajectories with a low cost experimental setup T2 - ISMRM (International Society for Magnetic Resonance in Medicine), 23rd Annual Meeting 2015, Toronto, Canada Y1 - 2015 ER - TY - GEN A1 - Harks, Tobias A1 - Heinz, Stefan A1 - Pfetsch, Marc T1 - Competitive Online Multicommodity Routing N2 - 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. T3 - ZIB-Report - 06-27 KW - Online Optimization KW - Routing KW - Telecommunications Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-9212 ER - TY - GEN A1 - Harks, Tobias A1 - Heinz, Stefan A1 - Pfetsch, Marc T1 - Competitive Online Multicommodity Routing N2 - 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. T3 - ZIB-Report - 07-16 KW - Online Optimization KW - Routing KW - Telecommunications Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-9599 ER - TY - GEN A1 - Bertelmann, Roland A1 - Koch, Thorsten A1 - Ceynowa, Klaus A1 - Söllner, Konstanze A1 - Christof, Jürgen A1 - Rusch, Beate A1 - Schäffler, Hildegard A1 - Putnings, Markus A1 - Pampel, Heinz A1 - Kuberek, Monika A1 - Boltze, Julia A1 - Lohrum, Stefan A1 - Retter, Regina A1 - Höllerl, Annika A1 - Faensen, Katja A1 - Steffen, Ronald A1 - Gross, Matthias A1 - Hoffmann, Cornelia A1 - Haoua, Marsa T1 - DeepGreen: Etablierung und Weiterentwicklung rechtssicherer Workflows zur effizienten Umsetzung von Open-Access-Komponenten in Lizenzvereinbarungen für wissenschaftliche Publikationen – Abschlussbericht N2 - DeepGreen wurde vom 01.08.2018 bis zum 30.06.2021 in einer zweiten Projektphase von der Deutschen Forschungsgemeinschaft (DFG) gefördert. DeepGreen unterstützt Bibliotheken als Dienstleister für Hochschulen, außeruniversitäre Forschungseinrichtungen und die dort tätigen Wissenschaftler:innen dabei, Publikationen auf Open-Access-Repositorien frei zugänglich zu machen und fördert das Zusammenspiel von wissenschaftlichen Einrichtungen und Verlagen. An der zweiten Projektphase waren der Kooperative Bibliotheksverbund Berlin-Brandenburg, die Bayerische Staatsbibliothek, der Bibliotheksverbund Bayern, die Universitätsbibliotheken der Friedrich-Alexander-Universität Erlangen-Nürnberg und der Technischen Universität Berlin und das Helmholtz Open Science Office beteiligt. In dem Projekt wurde erfolgreich eine technische und organisatorische Lösung zur automatisierten Verteilung von Artikeldaten wissenschaftlicher Verlage an institutionelle und fachliche Repositorien entwickelt. In der zweiten Projektphase lag der Fokus auf der Erprobung der Datendrehscheibe in der Praxis und der Ausweitung auf weitere Datenabnehmer und weitere Verlage. Im Anschluss an die DFG-geförderte Projektlaufzeit ist DeepGreen in einen zweijährigen Pilotbetrieb übergegangen. Ziel des Pilotbetriebs ist es, den Übergang in einen bundesweiten Real-Betrieb vorzubereiten. T3 - ZIB-Report - 21-37 KW - Open Access KW - Repositorien KW - DeepGreen Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-85420 SN - 1438-0064 ER - TY - GEN A1 - Bertelmann, Roland A1 - Boltze, Julia A1 - Ceynowa, Klaus A1 - Christof, Jürgen A1 - Faensen, Katja A1 - Groß, Matthias A1 - Hoffmann, Cornelia A1 - Koch, Thorsten A1 - Kuberek, Monika A1 - Lohrum, Stefan A1 - Pampel, Heinz A1 - Putnings, Markus A1 - Retter, Regina A1 - Rusch, Beate A1 - Schäffler, Hildegard A1 - Söllner, Konstanze A1 - Steffen, Ronald A1 - Wannick, Eike T1 - DeepGreen: Open-Access-Transformation in der Informationsinfrastruktur – Anforderungen und Empfehlungen, Version 1.0 N2 - DeepGreen ist ein Service, der es teilnehmenden institutionellen Open-Access-Repositorien,Open-Access-Fachrepositorien und Forschungsinformationssystemen erleichtert, für sie relevante Verlagspublikationen in zyklischer Abfolge mithilfe von Schnittstellen Open Access zur Verfügung zu stellen. Die entsprechende Bandbreite an Relationen zwischen den Akteuren, diverse lizenzrechtliche Rahmenbedingungen sowie technische Anforderungen gestalten das Thema komplex. Ziel dieser Handreichung ist es, neben all diesen Themen, die begleitend beleuchtet werden, im Besonderen Empfehlungen für die reibungslose Nutzung der Datenübertragung zu liefern. Außerdem werden mithilfe einer vorangestellten Workflow- Evaluierung Unterschiede und Besonderheiten in den Arbeitsschritten bei institutionellen Open-Access-Repositorien und Open-Access-Fachrepositorien aufgezeigt und ebenfalls mit Empfehlungen angereichert. T3 - ZIB-Report - 21-03 KW - Open Access KW - Zweitveröffentlichung KW - Bibliotheken KW - Verlage Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-81503 SN - 1438-0064 ER - TY - JOUR A1 - Boltze, Julia A1 - Höllerl, Annika A1 - Kuberek, Monika A1 - Lohrum, Stefan A1 - Pampel, Heinz A1 - Putnings, Markus A1 - Retter, Regina A1 - Rusch, Beate A1 - Schäffler, Hildegard A1 - Söllner, Konstanze T1 - DeepGreen: Eine Infrastruktur für die Open-Access-Transformation JF - O-Bib. Das Offene Bibliotheksjournal N2 - Mit DeepGreen wurde eine Infrastruktur aufgebaut und etabliert, die Zeitschriftenartikel von wissenschaftlichen Verlagen abholt und berechtigten Bibliotheken zur Veröffentlichung in ihren Repositorien sendet. DeepGreen unterstützt Bibliotheken als Dienstleister für Hochschulen, außeruniversitäre Einrichtungen und die dort tätigen Wissenschaftler*innen, Publikationen auf Open-Access-Repositorien frei zugänglich zu machen und fördert das Zusammenspiel von wissenschaftlichen Einrichtungen und Verlagen. DeepGreen wurde von Januar 2016 bis Juni 2021 von der Deutschen Forschungsgemeinschaft gefördert und wird nun vom Kooperativen Bibliotheksverbund Berlin-Brandenburg, von der Bayerischen Staatsbibliothek und von der Universitätsbibliothek Erlangen-Nürnberg in arbeitsteiliger Eigenleistung für zwei Jahre weiterbetrieben. Der vorliegende Beitrag beleuchtet vielfältige Aspekte bei der Realisierung von DeepGreen und geht auf die Perspektiven dieser zentralen Open-Access-Infrastruktur für deutsche Wissenschaftseinrichtungen ein. Y1 - 2022 U6 - https://doi.org/10.5282/o-bib/5764 VL - 9 IS - 1 ER - TY - JOUR A1 - Koch, Thorsten A1 - Achterberg, Tobias A1 - Andersen, Erling A1 - Bastert, Oliver A1 - Berthold, Timo A1 - Bixby, Robert E. A1 - Danna, Emilie A1 - Gamrath, Gerald A1 - Gleixner, Ambros A1 - Heinz, Stefan A1 - Lodi, Andrea A1 - Mittelmann, Hans A1 - Ralphs, Ted A1 - Salvagnin, Domenico A1 - Steffy, Daniel A1 - Wolter, Kati T1 - MIPLIB 2010 JF - Mathematical Programming Computation Y1 - 2011 UR - http://mpc.zib.de/index.php/MPC/article/view/56 U6 - https://doi.org/10.1007/s12532-011-0025-9 VL - 3 IS - 2 SP - 103 EP - 163 ER - TY - GEN A1 - Heinz, Stefan A1 - Schlechte, Thomas A1 - Stephan, Rüdiger A1 - Winkler, Michael T1 - Solving steel mill slab design problems N2 - The steel mill slab design problem from the CSPLIB is a combinatorial optimization problem motivated by an application of the steel industry. It has been widely studied in the constraint programming community. Several methods were proposed to solve this problem. A steel mill slab library was created which contains 380 instances. A closely related binpacking problem called the multiple knapsack problem with color constraints, originated from the same industrial problem, was discussed in the integer programming community. In particular, a simple integer program for this problem has been given by Forrest et al. The aim of this paper is to bring these different studies together. Moreover, we adapt the model of Forrest et al. for the steel mill slab design problem. Using this model and a state-of-the-art integer program solver all instances of the steel mill slab library can be solved efficiently to optimality. We improved, thereby, the solution values of 76 instances compared to previous results. Finally, we consider a recently introduced variant of the steel mill slab design problem, where within all solutions which minimize the leftover one is interested in a solution which requires a minimum number of slabs. For that variant we introduce two approaches and solve all instances of the steel mill slab library with this slightly changed objective function to optimality. T3 - ZIB-Report - 11-38 KW - steel mill slab design problem KW - multiple knapsack problem with color constraints KW - integer programming KW - set partitioning KW - binpacking with side constraints Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-14089 SN - 1438-0064 ER - TY - GEN A1 - Shinano, Yuji A1 - Achterberg, Tobias A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Koch, Thorsten T1 - ParaSCIP - a parallel extension of SCIP N2 - Mixed integer programming (MIP) has become one of the most important techniques in Operations Research and Discrete Optimization. SCIP (Solving Constraint Integer Programs) is currently one of the fastest non-commercial MIP solvers. It is based on the branch-and-bound procedure in which the problem is recursively split into smaller subproblems, thereby creating a so-called branching tree. We present ParaSCIP, an extension of SCIP, which realizes a parallelization on a distributed memory computing environment. ParaSCIP uses SCIP solvers as independently running processes to solve subproblems (nodes of the branching tree) locally. This makes the parallelization development independent of the SCIP development. Thus, ParaSCIP directly profits from any algorithmic progress in future versions of SCIP. Using a first implementation of ParaSCIP, we were able to solve two previously unsolved instances from MIPLIB2003, a standard test set library for MIP solvers. For these computations, we used up to 2048 cores of the HLRN~II supercomputer. T3 - ZIB-Report - 10-27 KW - massive parallization KW - mixed integer programming KW - ParaSCIP KW - branch-and-cut KW - branch-and-bound Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-11921 UR - http://www.springerlink.com/content/t2160206253v7661/ ER - TY - CHAP A1 - Heinz, Stefan A1 - Schulz, Jens T1 - Explanations for the Cumulative Constraint: An Experimental Study T2 - Experimental Algorithms Y1 - 2011 VL - 6630 SP - 400 EP - 409 ER - TY - CHAP A1 - Berthold, Timo A1 - Gleixner, Ambros A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Shinano, Yuji T1 - SCIP Optimization Suite を利用した 混合整数(線形/非線形) 計画問題の解法 T2 - Proceedings of the 24th RAMP symposium. The Operations Society of Japan, RAMP: Research Association of Mathematical Programming N2 - この論文ではソフトウェア・パッケージSCIP Optimization Suite を紹介し,その3つの構成要素:モデリン グ言語Zimpl, 線形計画(LP: linear programming) ソルバSoPlex, そして,制約整数計画(CIP: constraint integer programming) に対するソフトウェア・フレームワークSCIP, について述べる.本論文では,この3つの 構成要素を利用して,どのようにして挑戦的な混合整数線形計画問題(MIP: mixed integer linear optimization problems) や混合整数非線形計画問題(MINLP: mixed integer nonlinear optimization problems) をモデル化 し解くのかを説明する.SCIP は,現在,最も高速なMIP,MINLP ソルバの1つである.いくつかの例により, Zimpl, SCIP, SoPlex の利用方法を示すとともに,利用可能なインタフェースの概要を示す.最後に,将来の開 発計画の概要について述べる. N2 - This paper introduces the SCIP Optimization Suite and discusses the capabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming framework SCIP. We explain how in concert these can be used to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, we give an overview over available interfaces, and outline plans for future development. Y1 - 2012 SP - 165 EP - 192 ER - TY - CHAP A1 - Heinz, Stefan A1 - Beck, J. Christopher T1 - Reconsidering Mixed Integer Programming and MIP-based Hybrids for Scheduling T2 - Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2012) Y1 - 2012 VL - 7298 SP - 211 EP - 227 ER - TY - CHAP A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Schulz, Jens T1 - An approximative Criterion for the Potential of Energetic Reasoning T2 - Theory and Practice of Algorithms in (Computer) Systems Y1 - 2011 VL - 6595 SP - 229 EP - 239 ER - TY - JOUR A1 - Heinz, Stefan A1 - Schlechte, Thomas A1 - Stephan, Rüdiger A1 - Winkler, Michael T1 - Solving steel mill slab design problems JF - Constraints N2 - The steel mill slab design problem from the CSPLIB is a combinatorial optimization problem motivated by an application of the steel industry. It has been widely studied in the constraint programming community. Several methods were proposed to solve this problem. A steel mill slab library was created which contains 380 instances. A closely related binpacking problem called the multiple knapsack problem with color constraints, originated from the same industrial problem, was discussed in the integer programming community. In particular, a simple integer program for this problem has been given by Forrest et al. (INFORMS J Comput 18:129–134, 2006). The aim of this paper is to bring these different studies together. Moreover, we adapt the model of Forrest et al. (INFORMS J Comput 18:129–134, 2006) for the steel mill slab design problem. Using this model and a state-of-the-art integer program solver all instances of the steel mill slab library can be solved efficiently to optimality. We improved, thereby, the solution values of 76 instances compared to previous results (Schaus et al., Constraints 16:125–147, 2010). Finally, we consider a recently introduced variant of the steel mill slab design problem, where within all solutions which minimize the leftover one is interested in a solution which requires a minimum number of slabs. For that variant we introduce two approaches and solve all instances of the steel mill slab library with this slightly changed objective function to optimality. Y1 - 2012 U6 - https://doi.org/10.1007/s10601-011-9113-8 VL - 17 IS - 1 SP - 39 EP - 50 ER - TY - GEN A1 - Shinano, Yuji A1 - Achterberg, Tobias A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Winkler, Michael T1 - Solving hard MIPLIB2003 problems with ParaSCIP on Supercomputers: An update N2 - Contemporary supercomputers can easily provide years of CPU time per wall-clock hour. One challenge of today's software development is how to harness this wast computing power in order to solve really hard mixed integer programming instances. In 2010, two out of six open MIPLIB2003 instances could be solved by ParaSCIP in more than ten consecutive runs, restarting from checkpointing files. The contribution of this paper is threefold: For the first time, we present computational results of single runs for those two instances. Secondly, we provide new improved upper and lower bounds for all of the remaining four open MIPLIB2003 instances. Finally, we explain which new developments led to these results and discuss the current progress of ParaSCIP. Experiments were conducted on HLRNII, on HLRN III, and on the Titan supercomputer, using up to 35,200 cores. T3 - ZIB-Report - 13-66 KW - Mixed Integer Programming KW - MIPLIB2003 KW - ParaSCIP KW - Ubiquity Generator Framework KW - Supercomputer Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-42888 SN - 1438-0064 ER - TY - CHAP A1 - Heinz, Stefan A1 - Krumke, Sven A1 - Megow, Nicole A1 - Rambau, Jörg A1 - Tuchscherer, Andreas A1 - Vredeveld, Tjark ED - Erlebach, Thomas ED - Persiano, Giuseppe T1 - The Online Target Date Assignment Problem T2 - Proc. 3rd Workshop on Approximation and Online Algorithms Y1 - 2006 UR - http://opus.kobv.de/zib/volltexte/2005/894/ VL - 3879 SP - 230 EP - 243 PB - Springer ER - TY - JOUR A1 - Heinz, Stefan A1 - Kaibel, Volker A1 - Peinhardt, Matthias A1 - Rambau, Jörg A1 - Tuchscherer, Andreas T1 - LP-Based Local Approximation for Markov Decision Problems Y1 - 2006 IS - 343 PB - Matheon ER - TY - CHAP A1 - Shinano, Yuji A1 - Achterberg, Tobias A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Koch, Thorsten ED - Bischof, Christian ED - Hegering, Heinz-Gerd ED - Nagel, Wolfgang ED - Wittum, Gabriel T1 - ParaSCIP: a parallel extension of SCIP T2 - Competence in High Performance Computing 2010 Y1 - 2012 U6 - https://doi.org/10.1007/978-3-642-24025-6_12 SP - 135 EP - 148 PB - Springer ER - TY - GEN A1 - Heinz, Stefan A1 - Ku, Wen-Yang A1 - Beck, J. Christopher T1 - Recent improvements using constraint integer programming for resource allocation and scheduling N2 - Recently, we compared the performance of mixed-integer programming (MIP), constraint programming (CP), and constraint integer programming (CIP) to a state-of-the-art logic-based Benders manual decomposition (LBBD) for a resource allocation/scheduling problem. For a simple linear relaxation, the LBBD and CIP models deliver comparable performance with MIP also performing well. Here we show that algorithmic developments in CIP plus the use of an existing tighter relaxation substantially improve one of the CIP approaches. Furthermore, the use of the same relaxation in LBBD and MIP models significantly improves their performance. While such a result is known for LBBD, to the best of our knowledge, the other results are novel. Our experiments show that both CIP and MIP approaches are competitive with LBBD in terms of the number of problems solved to proven optimality, though MIP is about three times slower on average. Further, unlike the LBBD and CIP approaches, the MIP model is able to obtain provably high-quality solutions for all problem instances. T3 - ZIB-Report - 13-05 KW - constraint integer programming KW - constraint programming KW - cumulative constraint KW - mixed integer programming KW - optional activities Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-17676 SN - 1438-0064 ER - TY - GEN A1 - Heinz, Stefan A1 - Beck, J. Christopher T1 - Solving Resource Allocation/Scheduling Problems with Constraint Integer Programming N2 - Constraint Integer Programming (CIP) is a generalization of mixed-integer programming (MIP) in the direction of constraint programming (CP) allowing the inference techniques that have traditionally been the core of \P to be integrated with the problem solving techniques that form the core of complete MIP solvers. In this paper, we investigate the application of CIP to scheduling problems that require resource and start-time assignments to satisfy resource capacities. The best current approach to such problems is logic-based Benders decomposition, a manual decomposition method. We present a CIP model and demonstrate that it achieves performance competitive to the decomposition while out-performing the standard MIP and CP formulations. T3 - ZIB-Report - 11-14 KW - constraint integer programming KW - cumulative constraint KW - optional resources KW - mixed integer programming KW - constraint programming Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-12691 ER - TY - GEN A1 - Heinz, Stefan A1 - Schulz, Jens T1 - Explanations for the Cumulative Constraint: an Experimental Study N2 - In cumulative scheduling, conflict analysis seems to be one of the key ingredients to solve such problems efficiently. Thereby, the computational complexity of explanation algorithms plays an important role. Even more when we are faced with a backtracking system where explanations need to be constructed on the fly. In this paper we present extensive computational results to analyze the impact of explanation algorithms for the cumulative constraint in a backward checking system. The considered explanation algorithms differ in their quality and computational complexity. We present results for the domain propagation algorithms time-tabling, edge-finding, and energetic reasoning. T3 - ZIB-Report - 11-13 KW - conflict analysis KW - constraint integer programming KW - cumulative constraint KW - resource-constrained project scheduling KW - propagation algorithms Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-12668 ER - TY - CHAP A1 - Shinano, Yuji A1 - Berthold, Timo A1 - Heinz, Stefan T1 - A First Implementation of ParaXpress: Combining Internal and External Parallelization to Solve MIPs on Supercomputers T2 - Mathematical Software - ICMS 2016, 5th International Conference Berlin, Germany, July 11-14, 2016 Proceedings Y1 - 2016 U6 - https://doi.org/10.1007/978-3-319-42432-3_38 SP - 308 EP - 316 ER - TY - CHAP A1 - Berthold, Timo A1 - Farmer, James A1 - Heinz, Stefan A1 - Perregaard, Michael T1 - Parallelization of the FICO Xpress-Optimizer T2 - Mathematical Software - ICMS 2016, 5th International Conference Berlin, Germany, July 11-14, 2016 Proceedings Y1 - 2016 U6 - https://doi.org/10.1007/978-3-319-42432-3_31 SP - 251 EP - 258 ER - TY - JOUR A1 - Shinano, Yuji A1 - Berthold, Timo A1 - Heinz, Stefan T1 - ParaXpress: An Experimental Extension of the FICO Xpress-Optimizer to Solve Hard MIPs on Supercomputers JF - Optimization Methods & Software N2 - The Ubiquity Generator (UG) is a general framework for the external parallelization of mixed integer programming (MIP) solvers. In this paper, we present ParaXpress, a distributed memory parallelization of the powerful commercial MIP solver FICO Xpress. Besides sheer performance, an important feature of Xpress is that it provides an internal parallelization for shared memory systems. When aiming for a best possible performance of ParaXpress on a supercomputer, the question arises how to balance the internal Xpress parallelization and the external parallelization by UG against each other. We provide computational experiments to address this question and we show computational results for running ParaXpress on a Top500 supercomputer, using up to 43,344 cores in parallel. Y1 - 2018 U6 - https://doi.org/10.1080/10556788.2018.1428602 VL - 33 IS - 3 SP - 530 EP - 539 ER - TY - GEN A1 - Berthold, Timo A1 - Gleixner, Ambros A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Shinano, Yuji T1 - SCIP Optimization Suite を利用した 混合整数(線形/非線形) 計画問題の解法 T1 - Solving mixed integer linear and nonlinear problems using the SCIP Optimization Suite N2 - この論文ではソフトウェア・パッケージSCIP Optimization Suite を紹介し,その3つの構成要素:モデリン グ言語Zimpl, 線形計画(LP: linear programming) ソルバSoPlex, そして,制約整数計画(CIP: constraint integer programming) に対するソフトウェア・フレームワークSCIP, について述べる.本論文では,この3つの 構成要素を利用して,どのようにして挑戦的な混合整数線形計画問題(MIP: mixed integer linear optimization problems) や混合整数非線形計画問題(MINLP: mixed integer nonlinear optimization problems) をモデル化 し解くのかを説明する.SCIP は,現在,最も高速なMIP,MINLP ソルバの1つである.いくつかの例により, Zimpl, SCIP, SoPlex の利用方法を示すとともに,利用可能なインタフェースの概要を示す.最後に,将来の開 発計画の概要について述べる. N2 - This paper introduces the SCIP Optimization Suite and discusses the capabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming framework SCIP. We explain how in concert these can be used to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, we give an overview over available interfaces, and outline plans for future development. T3 - ZIB-Report - 12-24 KW - SCIP, MIP, MINLP, CIP, LP, modeling, optimization Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-15598 SN - 1438-0064 ER - TY - GEN A1 - Heinz, Stefan A1 - Sachenbacher, Martin T1 - Using Model Counting to Find Optimal Distinguishing Tests N2 - Testing is the process of stimulating a system with inputs in order to reveal hidden parts of the system state. In the case of non-deterministic systems, the difficulty arises that an input pattern can generate several possible outcomes. Some of these outcomes allow to distinguish between different hypotheses about the system state, while others do~not. In this paper, we present a novel approach to find, for non-deterministic systems modeled as constraints over variables, tests that allow to distinguish among the hypotheses as good as possible. The idea is to assess the quality of a test by determining the ratio of distinguishing (good) and not distinguishing (bad) outcomes. This measure refines previous notions proposed in the literature on model-based testing and can be computed using model counting techniques. We propose and analyze a greedy-type algorithm to solve this test optimization problem, using existing model counters as a building block. We give preliminary experimental results of our method, and discuss possible improvements. T3 - ZIB-Report - 08-32 KW - zählen KW - automatische Test Generierung KW - counting KW - automated test generation KW - constraint programming Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-10832 SN - 1438-0064 ER - TY - GEN A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Pfetsch, Marc T1 - Solving Pseudo-Boolean Problems with SCIP N2 - 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. T3 - ZIB-Report - 08-12 KW - Pseudo-Boolean KW - Constraint Programming KW - Ganzzahlige Programmierung KW - Branch-And-Cut KW - Optimierungssoftware KW - Pseudo-Boolean KW - constraint integer programming KW - integer programming KW - branch-and-cut KW - optimization software Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-10671 SN - 1438-0064 ER - TY - GEN A1 - Achterberg, Tobias A1 - Heinz, Stefan A1 - Koch, Thorsten T1 - Counting solutions of integer programs using unrestricted subtree detection N2 - In the recent years there has been tremendous progress in the development of algorithms to find optimal solutions for integer programs. In many applications it is, however, desirable (or even necessary) to generate all feasible solutions. Examples arise in the areas of hardware and software verification and discrete geometry. In this paper, we investigate how to extend branch-and-cut integer programming frameworks to support the generation of all solutions. We propose a method to detect so-called unrestricted subtrees, which allows us to prune the integer program search tree and to collect several solutions simultaneously. We present computational results of this branch-and-count paradigm which show the potential of the unrestricted subtree detection. T3 - ZIB-Report - 08-09 KW - Zählen KW - ganzzahlige Programme KW - IP KW - counting KW - integer programming KW - IP Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-10632 SN - 1438-0064 ER - TY - THES A1 - Heinz, Stefan T1 - Policies for Online Target Date Assignment Problems: Competitive Analysis versus Expected Performance Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-9933 ER - TY - CHAP A1 - Shinano, Yuji A1 - Achterberg, Tobias A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Winkler, Michael T1 - Solving Open MIP Instances with ParaSCIP on Supercomputers using up to 80,000 Cores T2 - Proc. of 30th IEEE International Parallel & Distributed Processing Symposium N2 - This paper describes how we solved 12 previously unsolved mixed-integer program- ming (MIP) instances from the MIPLIB benchmark sets. To achieve these results we used an enhanced version of ParaSCIP, setting a new record for the largest scale MIP computation: up to 80,000 cores in parallel on the Titan supercomputer. In this paper we describe the basic parallelization mechanism of ParaSCIP, improvements of the dynamic load balancing and novel techniques to exploit the power of parallelization for MIP solving. We give a detailed overview of computing times and statistics for solving open MIPLIB instances. Y1 - 2016 U6 - https://doi.org/10.1109/IPDPS.2016.56 ER - TY - GEN A1 - Harks, Tobias A1 - Heinz, Stefan A1 - Pfetsch, Marc A1 - Vredeveld, Tjark T1 - Online Multicommodity Routing with Time Windows N2 - 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. T3 - ZIB-Report - 07-22 KW - Online Optimization KW - Routing KW - Telecommunications Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-9654 SN - 1438-0064 ER - TY - GEN A1 - Koch, Thorsten A1 - Achterberg, Tobias A1 - Andersen, Erling A1 - Bastert, Oliver A1 - Berthold, Timo A1 - Bixby, Robert E. A1 - Danna, Emilie A1 - Gamrath, Gerald A1 - Gleixner, Ambros A1 - Heinz, Stefan A1 - Lodi, Andrea A1 - Mittelmann, Hans A1 - Ralphs, Ted A1 - Salvagnin, Domenico A1 - Steffy, Daniel A1 - Wolter, Kati T1 - MIPLIB 2010 N2 - This paper reports on the fifth version of the Mixed Integer Programming Library. The MIPLIB 2010 is the first MIPLIB release that has been assembled by a large group from academia and from industry, all of whom work in integer programming. There was mutual consent that the concept of the library had to be expanded in order to fulfill the needs of the community. The new version comprises 361 instances sorted into several groups. This includes the main benchmark test set of 87 instances, which are all solvable by today's codes, and also the challenge test set with 164 instances, many of which are currently unsolved. For the first time, we include scripts to run automated tests in a predefined way. Further, there is a solution checker to test the accuracy of provided solutions using exact arithmetic. T3 - ZIB-Report - 10-31 KW - Mixed Integer Programming KW - Problem Instances KW - IP KW - MIP KW - MIPLIB Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-12953 ER - TY - GEN A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Schulz, Jens T1 - An approximative Criterion for the Potential of Energetic Reasoning N2 - Energetic reasoning is one of the most powerful propagation algorithms in cumulative scheduling. In practice, however, it is not commonly used because it has a high running time and its success highly depends on the tightness of the variable bounds. In order to speed up energetic reasoning, we provide an easy-to-check necessary condition for energetic reasoning to detect infeasibilities. We present an implementation of energetic reasoning that employs this condition and that can be parametrically adjusted to handle the trade-off between solving time and propagation overhead. Computational results on instances from the PSPLIB are provided. These results show that using this condition decreases the running time by more than a half, although more search nodes need to be explored. T3 - ZIB-Report - 11-12 KW - conflict analysis KW - constraint integer programming KW - cumulative constraint KW - resource-constrained project scheduling KW - energetic reasoning Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-12655 ER - TY - CHAP A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Lübbecke, Marco A1 - Möhring, Rolf A1 - Schulz, Jens ED - Lodi, Andrea ED - Milano, Michela ED - Toth, Paolo T1 - A Constraint Integer Programming Approach for Resource-Constrained Project Scheduling T2 - Proc. of CPAIOR 2010 Y1 - 2010 VL - 6140 SP - 313 EP - 317 PB - Springer ER - TY - CHAP A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Pfetsch, Marc ED - Kullmann, Oliver T1 - Nonlinear pseudo-Boolean optimization T2 - Theory and Applications of Satisfiability Testing – SAT 2009 Y1 - 2009 VL - 5584 SP - 441 EP - 446 PB - Springer ER - TY - GEN A1 - Heinz, Stefan A1 - Schulz, Jens A1 - Beck, J. Christopher T1 - Using dual presolving reductions to reformulate cumulative constraints N2 - Dual presolving reductions are a class of reformulation techniques that remove feasible or even optimal solutions while guaranteeing that at least one optimal solution remains, as long as the original problem was feasible. Presolving and dual reductions are important components of state-of-the-art mixed-integer linear programming solvers. In this paper, we introduce them both as unified, practical concepts in constraint programming solvers. Building on the existing idea of variable locks, we formally define and justify the use of dual information for cumulative constraints during a presolving phase of a solver. In particular, variable locks are used to decompose cumulative constraints, detect irrelevant variables, and infer variable assignments and domain reductions. Since the computational complexity of propagation algorithms typically depends on the number of variables and/or domain size, such dual reductions are a source of potential computational speed-up. Through experimental evidence on resource constrained project scheduling problems, we demonstrate that the conditions for dual reductions are present in well-known benchmark instances and that a substantial proportion of them can be solved to optimality in presolving -- without search. While we consider this result very promising, we do not observe significant change in overall run-time from the use of our novel dual reductions. T3 - ZIB-Report - 12-37 KW - dual reductions KW - cumulative constraints KW - presolving KW - variable locks Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-16321 SN - 1438-0064 ER - TY - GEN A1 - Berthold, Timo A1 - Gamrath, Gerald A1 - Gleixner, Ambros A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Shinano, Yuji T1 - Solving mixed integer linear and nonlinear problems using the SCIP Optimization Suite N2 - This paper introduces the SCIP Optimization Suite and discusses the capabilities of its three components: the modeling language Zimpl, the linear programming solver SoPlex, and the constraint integer programming framework SCIP. We explain how these can be used in concert to model and solve challenging mixed integer linear and nonlinear optimization problems. SCIP is currently one of the fastest non-commercial MIP and MINLP solvers. We demonstrate the usage of Zimpl, SCIP, and SoPlex by selected examples, we give an overview of available interfaces, and outline plans for future development. T3 - ZIB-Report - 12-27 KW - LP, MIP, CIP, MINLP, modeling, optimization, SCIP, SoPlex, Zimpl Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-15654 SN - 1438-0064 ER - TY - GEN A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Lübbecke, Marco A1 - Möhring, Rolf A1 - Schulz, Jens T1 - A Constraint Integer Programming Approach for Resource-Constrained Project Scheduling N2 - We propose a hybrid approach for solving the resource-constrained project scheduling problem which is an extremely hard to solve combinatorial optimization problem of practical relevance. Jobs have to be scheduled on (renewable) resources subject to precedence constraints such that the resource capacities are never exceeded and the latest completion time of all jobs is minimized. The problem has challenged researchers from different communities, such as integer programming (IP), constraint programming (CP), and satisfiability testing (SAT). Still, there are instances with 60 jobs which have not been solved for many years. The currently best known approach, lazyFD, is a hybrid between CP and SAT techniques. In this paper we propose an even stronger hybridization by integrating all the three areas, IP, CP, and SAT, into a single branch-and-bound scheme. We show that lower bounds from the linear relaxation of the IP formulation and conflict analysis are key ingredients for pruning the search tree. First computational experiments show very promising results. For five instances of the well-known PSPLIB we report an improvement of lower bounds. Our implementation is generic, thus it can be potentially applied to similar problems as well. T3 - ZIB-Report - 10-03 KW - constraint integer programming KW - cumulative constraint KW - scheduling KW - conflict analysis KW - resource-constrained project Scheduling Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-11180 SN - 1438-0064 ER - TY - GEN A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Pfetsch, Marc T1 - Nonlinear pseudo-Boolean optimization: relaxation or propagation? N2 - 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. T3 - ZIB-Report - 09-11 KW - Pseudo-Boolean KW - constraint integer programming KW - linear relaxation KW - separation algorithm KW - domain propagation Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-11232 SN - 1438-0064 ER - TY - GEN A1 - Heinz, Stefan A1 - Stephan, Rüdiger A1 - Schlechte, Thomas T1 - Solving Steel Mill Slab Problems with Branch and Price N2 - The steel mill slab design problem from the CSPLib is a binpacking problem that is motivated by an application of the steel industry and that has been widely studied in the constraint programming community. Recently, several people proposed new models and methods to solve this problem. A steel mill slab library was created which contains 380 instances. A closely related binpacking problem called multiple knapsack problem with color constraints, originated from the same industrial problem, were discussed in the integer programming community. In particular, a simple integer programming for this problem has been given by Forrest et al. [3]. The aim of this paper is to bring these different studies together. Moreover, we adopt the model of [3] for the steel mill slab problem. Using a state of the art integer program solver, this model is capable to solve all instances of the steel mill slab library, mostly in less than one second, to optimality. We improved, thereby, the solution value of 76 instances. T3 - ZIB-Report - 09-14 KW - steel mill slab problem KW - branch-and-price KW - integer programming Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-11260 SN - 1438-0064 ER - TY - GEN A1 - Achterberg, Tobias A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Wolter, Kati T1 - Constraint Integer Programming: Techniques and Applications N2 - This article introduces constraint integer programming (CIP), which is a novel way to combine constraint programming (CP) and mixed integer programming (MIP) methodologies. CIP is a generalization of MIP that supports the notion of general constraints as in CP. This approach is supported by the CIP framework SCIP, which also integrates techniques for solving satisfiability problems. SCIP is available in source code and free for noncommercial use. We demonstrate the usefulness of CIP on three tasks. First, we apply the constraint integer programming approach to pure mixed integer programs. Computational experiments show that SCIP is almost competitive to current state-of-the-art commercial MIP solvers. Second, we demonstrate how to use CIP techniques to compute the number of optimal solutions of integer programs. Third, we employ the CIP framework to solve chip design verification problems, which involve some highly nonlinear constraint types that are very hard to handle by pure MIP solvers. The CIP approach is very effective here: it can apply the full sophisticated MIP machinery to the linear part of the problem, while dealing with the nonlinear constraints by employing constraint programming techniques. T3 - ZIB-Report - 08-43 KW - constraint programming KW - mixed integer programming KW - branch-and-cut KW - optimization software KW - chip verification Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-10950 SN - 1438-0064 ER - TY - CHAP A1 - Witzig, Jakob A1 - Berthold, Timo A1 - Heinz, Stefan T1 - Experiments with Conflict Analysis in Mixed Integer Programming T2 - Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2017 N2 - The analysis of infeasible subproblems plays an import role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally different concepts to generate valid global constraints from infeasible subproblems. The first is to analyze the sequence of implications obtained by domain propagation that led to infeasibility. The result of the analysis is one or more sets of contradicting variable bounds from which so-called conflict constraints can be generated. This concept has its origin in solving satisfiability problems and is similarly used in constraint programming. The second concept is to analyze infeasible linear programming (LP) relaxations. The dual LP solution provides a set of multipliers that can be used to generate a single new globally valid linear constraint. The main contribution of this short paper is an empirical evaluation of two ways to combine both approaches. Experiments are carried out on general MIP instances from standard public test sets such as Miplib2010; the presented algorithms have been implemented within the non-commercial MIP solver SCIP. Moreover, we present a pool-based approach to manage conflicts which addresses the way a MIP solver traverses the search tree better than aging strategies known from SAT solving. Y1 - 2017 U6 - https://doi.org/10.1007/978-3-319-59776-8_17 VL - 10335 SP - 211 EP - 222 PB - Springer ER - TY - CHAP A1 - Shinano, Yuji A1 - Achterberg, Tobias A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Koch, Thorsten A1 - Winkler, Michael ED - IEEE, T1 - Solving Hard MIPLIP2003 Problems with ParaSCIP on Supercomputers: An Update T2 - IPDPSW'14 Proceedings of the 2014 IEEE, International Parallel & Distributed Processing Symposium Workshops Y1 - 2014 SN - 978-1-4799-4117-9 U6 - https://doi.org/10.1109/IPDPSW.2014.174 SP - 1552 EP - 1561 PB - IEEE Computer Society CY - Washington, DC, USA ER - TY - GEN A1 - Gamrath, Gerald A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Winkler, Michael T1 - Structure-based primal heuristics for mixed integer programming N2 - Primal heuristics play an important role in the solving of mixed integer programs (MIPs). They help to reach optimality faster and provide good feasible solutions early in the solving process. In this paper, we present two new primal heuristics which take into account global structures available within MIP solvers to construct feasible solutions at the beginning of the solving process. These heuristics follow a large neighborhood search (LNS) approach and use global structures to define a neighborhood that is with high probability significantly easier to process while (hopefully) still containing good feasible solutions. The definition of the neighborhood is done by iteratively fixing variables and propagating these fixings. Thereby, fixings are determined based on the predicted impact they have on the subsequent domain propagation. The neighborhood is solved as a sub-MIP and solutions are transferred back to the original problem. Our computational experiments on standard MIP test sets show that the proposed heuristics find solutions for about every third instance and therewith help to improve the average solving time. T3 - ZIB-Report - 15-26 KW - mixed-integer programming, large neighborhood search, primal heuristics, domain propagation Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-55518 SN - 1438-0064 ER - TY - GEN A1 - Gamrath, Gerald A1 - Berthold, Timo A1 - Heinz, Stefan A1 - Winkler, Michael T1 - Structure-driven fix-and-propagate heuristics for mixed integer programming N2 - Primal heuristics play an important role in the solving of mixed integer programs (MIPs). They often provide good feasible solutions early in the solving process and help to solve instances to optimality faster. In this paper, we present a scheme for primal start heuristics that can be executed without previous knowledge of an LP solution or a previously found integer feasible solution. It uses global structures available within MIP solvers to iteratively fix integer variables and propagate these fixings. Thereby, fixings are determined based on the predicted impact they have on the subsequent domain propagation. If sufficiently many variables can be fixed that way, the resulting problem is solved as an LP and the solution is rounded. If the rounded solution did not provide a feasible solution already, a sub-MIP is solved for the neighborhood defined by the variable fixings performed in the first phase. The global structures help to define a neighborhood that is with high probability significantly easier to process while (hopefully) still containing good feasible solutions. We present three primal heuristics that use this scheme based on different global structures. Our computational experiments on standard MIP test sets show that the proposed heuristics find solutions for about three out of five instances and therewith help to improve several performance measures for MIP solvers, including the primal integral and the average solving time. T3 - ZIB-Report - 17-56 KW - mixed-integer programming KW - primal heuristics KW - fix-and-propagate KW - large neighborhood search KW - domain propagation Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-65387 SN - 1438-0064 ER - TY - GEN A1 - Heinz, Stefan A1 - Beck, J. Christopher T1 - Reconsidering Mixed Integer Programming and MIP-based Hybrids for Scheduling N2 - Despite the success of constraint programming (CP) for scheduling, the much wider penetration of mixed integer programming (MIP) technology into business applications means that many practical scheduling problems are being addressed with MIP, at least as an initial approach. Furthermore, there has been impressive and well-documented improvements in the power of generic MIP solvers over the past decade. We empirically demonstrate that on an existing set of resource allocation and scheduling problems standard MIP and CP models are now competitive with the state-of-the-art manual decomposition approach. Motivated by this result, we formulate two tightly coupled hybrid models based on constraint integer programming (CIP) and demonstrate that these models, which embody advances in CP and MIP, are able to out-perform the CP, MIP, and decomposition models. We conclude that both MIP and CIP are technologies that should be considered along with CP for solving scheduling problems. T3 - ZIB-Report - 12-05 KW - constraint integer programming KW - constraint programming KW - cumulative constraint KW - mixed integer programming KW - optional activities Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-14660 SN - 1438-0064 ER -