869
eng
reportzib
0
2005-08-01
2005-08-01
--
Optimal Fares for Public Transport
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.
05-35
869
urn:nbn:de:0297-zib-8698
Appeared in: Operations Research Proceedings 2005. H.-D. Haasis et al. (eds.) Springer 2006, 591-596
Ralf Borndörfer
Marika Neumann
Marc Pfetsch
ZIB-Report
05-35
eng
uncontrolled
fare planning
eng
uncontrolled
demand function
eng
uncontrolled
discrete choice model
Informatik, Informationswissenschaft, allgemeine Werke
Traffic problems
Models of real-world systems
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B1
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/869/ZR-05-35.pdf
https://opus4.kobv.de/opus4-zib/files/869/ZR-05-35.ps
870
eng
reportzib
0
2005-08-01
2005-08-01
--
Routing in Line Planning for Public Transportation
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.
05-36
870
urn:nbn:de:0297-zib-8706
Appeared in: Operations Research Proceedings 2005. H.-D. Haasis et al. (eds.) Springer 2006, 405-410
Marc Pfetsch
Ralf Borndörfer
ZIB-Report
05-36
eng
uncontrolled
line planning
eng
uncontrolled
column generation
eng
uncontrolled
passenger routing
Informatik, Informationswissenschaft, allgemeine Werke
Transportation, logistics
Combinatorial optimization
ZIB Allgemein
Borndörfer, Ralf
MATHEON-B1
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/870/ZR-05-36.pdf
https://opus4.kobv.de/opus4-zib/files/870/ZR-05-36.ps
879
eng
reportzib
0
2005-11-11
2005-11-11
--
A Branch-And-Cut for the Maximum Feasible Subsystem Problem
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.
05-46
879
urn:nbn:de:0297-zib-8797
Appeared in: SIAM J. Optimization 19 (2008) 21-38
Marc Pfetsch
ZIB-Report
05-46
eng
uncontrolled
infeasible linear inequality system
eng
uncontrolled
irreducible infeasible subsystem
eng
uncontrolled
(IIS) maximum feasible subsystem problem
eng
uncontrolled
minimum IIS-cover
eng
uncontrolled
branch-and-cut
Informatik, Informationswissenschaft, allgemeine Werke
Combinatorial optimization
ZIB Allgemein
ZIB-Infeas
https://opus4.kobv.de/opus4-zib/files/879/ZR_05_46.pdf
https://opus4.kobv.de/opus4-zib/files/879/ZR-05-46.pdf
https://opus4.kobv.de/opus4-zib/files/879/ZR_05_46.ps
https://opus4.kobv.de/opus4-zib/files/879/ZR-05-46.ps
965
eng
reportzib
0
2007-08-13
2007-08-13
--
Online Multicommodity Routing with Time Windows
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.
07-22
1438-0064
976
urn:nbn:de:0297-zib-9654
Tobias Harks
unknown unknown
Stefan Heinz
Marc Pfetsch
Tjark Vredeveld
ZIB-Report
07-22
eng
uncontrolled
Online Optimization
eng
uncontrolled
Routing
eng
uncontrolled
Telecommunications
Informatik, Informationswissenschaft, allgemeine Werke
Analysis of algorithms [See also 68Q25]
Convex programming
Mathematical Optimization
Heinz, Stefan
https://opus4.kobv.de/opus4-zib/files/965/ZR_07_22.pdf
https://opus4.kobv.de/opus4-zib/files/965/ZR_07_22.ps
1055
deu
reportzib
0
2008-01-15
2008-01-15
--
Angebotsplanung im öffentlichen Nahverkehr
Service Design in Public Transport
Die Angebotsplanung im öffentlichen 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 für die Verkehrsbetriebe in Potsdam(ViP), dass sich damit komplexe Zusammenhänge quantitativ analysieren lassen. Auf diese Weise untersuchen wir die Auswirkungen von Freiheitsgraden auf die Konstruktion von Linien und die Wahl von Reisewegen der Passagiere, Abhängigkeiten zwischen Kosten und Reisezeiten sowie den Einfluss verschiedener Preissysteme auf Nachfrage und Kostendeckung.
08-04
1438-0064
1084
urn:nbn:de:0297-zib-10555
To appear in Heureka '08
Ralf Borndörfer
unknown unknown
Marika Neumann
Marc Pfetsch
ZIB-Report
08-04
deu
uncontrolled
Preisplanung
deu
uncontrolled
Linienplanung
deu
uncontrolled
Optimierung
Mathematik
Transportation, logistics
Traffic problems
Combinatorial optimization
Models of real-world systems
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/1055/ZR_08_04.pdf
921
eng
reportzib
0
2006-05-30
2006-05-30
--
Competitive Online Multicommodity Routing
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.
06-27
921
urn:nbn:de:0297-zib-9212
Appeared in: T. Erlebach and C. Kaklamanis (eds.) Approximation and Online Algorithms (WAOA 2006). LNCS 4368, pp. 240-252, 2007
Tobias Harks
Stefan Heinz
Marc Pfetsch
ZIB-Report
06-27
eng
uncontrolled
Online Optimization
eng
uncontrolled
Routing
eng
uncontrolled
Telecommunications
Informatik, Informationswissenschaft, allgemeine Werke
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
ZIB Allgemein
Heinz, Stefan
https://opus4.kobv.de/opus4-zib/files/921/ZR-06-27.pdf
https://opus4.kobv.de/opus4-zib/files/921/ZR-06-27.ps
785
eng
reportzib
0
2004-04-20
2004-04-20
--
Models for Line Planning in Public Transport
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.
04-10
786
urn:nbn:de:0297-zib-7854
10.1007/978-3-540-73312-6_18
Appeared in: Computer-aided Systems in Public Transport. Mark Hickman, Pitu Mirchandani, Stefan Voss (eds.) Lecture Notes in Economics and Mathematical Systems, 600, 2008, pp. 363-378
Ralf Borndörfer
Martin Grötschel
Marc Pfetsch
ZIB-Report
04-10
eng
uncontrolled
line planning
eng
uncontrolled
column generation
Informatik, Informationswissenschaft, allgemeine Werke
Transportation, logistics
Combinatorial optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
Grötschel, Martin
MATHEON-B1
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/785/ZR-04-10.ps
https://opus4.kobv.de/opus4-zib/files/785/ZR-04-10.pdf
1117
eng
reportzib
0
2009-02-24
2009-02-24
--
The Steiner Connectivity Problem
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.
09-07
1438-0064
1166
10.1007/s10107-012-0564-5
urn:nbn:de:0297-zib-11171
Ralf Borndörfer
unknown unknown
Marika Neumann
Marc Pfetsch
ZIB-Report
09-07
eng
uncontrolled
Steiner Tree
eng
uncontrolled
Partition Inequalities
eng
uncontrolled
Paths
eng
uncontrolled
Connectivity
eng
uncontrolled
Generalization
Informatik, Informationswissenschaft, allgemeine Werke
Combinatorial optimization
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/1117/ZR_09_07.pdf
https://opus4.kobv.de/opus4-zib/files/1117/ZR_09_07.ps
https://opus4.kobv.de/opus4-zib/files/1117/ZR-09-07revised.pdf
1298
eng
reportzib
0
2011-05-31
2011-05-31
--
Large Neighborhood Search beyond MIP
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.
11-21
urn:nbn:de:0297-zib-12989
Appeared in: Proceedings of the 9th Metaheuristics International Conference (MIC 2011). 2011. Luca di Gaspar et al. eds. ISBN 978-88-900984-3-7, pp. 51-60
Timo Berthold
Timo Berthold
Stefan Heinz
Marc Pfetsch
Stefan Vigerske
ZIB-Report
11-21
deu
uncontrolled
Large Neighborhood Search
deu
uncontrolled
Primal Heuristic
deu
uncontrolled
MIP
deu
uncontrolled
MIQCP
deu
uncontrolled
Pseudo-Boolean
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Mathematical Optimization
Berthold, Timo
Heinz, Stefan
Vigerske, Stefan
https://opus4.kobv.de/opus4-zib/files/1298/lns4cip.pdf
1123
eng
reportzib
0
2009-03-29
2009-03-29
--
Nonlinear pseudo-Boolean optimization: relaxation or propagation?
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.
09-11
1438-0064
1172
urn:nbn:de:0297-zib-11232
Appeared in: O. Kullmann (Ed.), Theory and Applications of Satisfiability Testing -- SAT 2009; Lecture Notes in Computer Science 5584, pp. 441-446, 2009
Timo Berthold
unknown unknown
Stefan Heinz
Marc Pfetsch
ZIB-Report
09-11
eng
uncontrolled
Pseudo-Boolean
eng
uncontrolled
constraint integer programming
eng
uncontrolled
linear relaxation
eng
uncontrolled
separation algorithm
eng
uncontrolled
domain propagation
Mathematik
Mathematical programming methods [See also 90Cxx]
Boolean programming
Integer programming
Nonlinear programming
Mathematical Optimization
Berthold, Timo
Heinz, Stefan
https://opus4.kobv.de/opus4-zib/files/1123/ZR_09_11.pdf
https://opus4.kobv.de/opus4-zib/files/1123/ZR_09_11.ps
959
eng
reportzib
0
2007-06-14
2007-06-14
--
Competitive Online Multicommodity Routing
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.
07-16
959
urn:nbn:de:0297-zib-9599
Appeared in: Theory of Computing Systems 45, No. 3 (2009), 533-554
Tobias Harks
Stefan Heinz
Marc Pfetsch
ZIB-Report
07-16
eng
uncontrolled
Online Optimization
eng
uncontrolled
Routing
eng
uncontrolled
Telecommunications
Informatik, Informationswissenschaft, allgemeine Werke
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
ZIB Allgemein
Heinz, Stefan
https://opus4.kobv.de/opus4-zib/files/959/ZR_07_16.pdf
https://opus4.kobv.de/opus4-zib/files/959/ZR-07-16.pdf
https://opus4.kobv.de/opus4-zib/files/959/ZR-07-16.ps
https://opus4.kobv.de/opus4-zib/files/959/ZR_07_16.ps
1082
eng
reportzib
0
2008-08-14
2008-08-14
--
The Line Connectivity Problem
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.
08-31
1438-0064
1117
urn:nbn:de:0297-zib-10820
Appeared in: Operations Reserach Proceedings 2008. Bernhard Fleischmann ... (eds.) Springer 2009, pp. 557-562
Ralf Borndörfer
unknown unknown
Marika Neumann
Marc Pfetsch
ZIB-Report
08-31
eng
uncontrolled
Steiner Tree Generalization
Mathematik
Combinatorial optimization
Mathematical Optimization
Borndörfer, Ralf
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/1082/ZR_08_31.pdf
https://opus4.kobv.de/opus4-zib/files/1082/ZR_08_31.ps
1084
eng
reportzib
0
2008-08-14
2008-08-14
--
Detecting Orbitopal Symmetries
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.
08-33
1438-0064
1119
urn:nbn:de:0297-zib-10842
Appeared in: Operations Research Proceedings 2008, Bernhard Fleischmann ... (eds.), 2009, pp. 433-438
Timo Berthold
unknown unknown
Marc Pfetsch
ZIB-Report
08-33
deu
uncontrolled
Symmetrie-Erkennung
deu
uncontrolled
Orbitope
deu
uncontrolled
Ganzzahlige Programmierung
deu
uncontrolled
Symmetrie-Brechung
deu
uncontrolled
Graphenisomorphie
eng
uncontrolled
symmetry detection
eng
uncontrolled
orbitopes
eng
uncontrolled
integer programming
eng
uncontrolled
symmetry breaking
eng
uncontrolled
graph ismorphism
Mathematik
Special polytopes (linear programming, centrally symmetric, etc.)
Integer programming
Programming involving graphs or networks [See also 90C27]
Polyhedral combinatorics, branch-and-bound, branch-and-cut
Mathematical Optimization
Berthold, Timo
MATHEON-B12:IPSym
https://opus4.kobv.de/opus4-zib/files/1084/ZR_08_33.pdf
https://opus4.kobv.de/opus4-zib/files/1084/ZR_08_33.ps
1067
eng
reportzib
0
2008-03-03
2008-03-03
--
Solving Pseudo-Boolean Problems with SCIP
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.
08-12
1438-0064
1095
urn:nbn:de:0297-zib-10671
Timo Berthold
unknown unknown
Stefan Heinz
Marc Pfetsch
ZIB-Report
08-12
deu
uncontrolled
Pseudo-Boolean
deu
uncontrolled
Constraint Programming
deu
uncontrolled
Ganzzahlige Programmierung
deu
uncontrolled
Branch-And-Cut
deu
uncontrolled
Optimierungssoftware
eng
uncontrolled
Pseudo-Boolean
eng
uncontrolled
constraint integer programming
eng
uncontrolled
integer programming
eng
uncontrolled
branch-and-cut
eng
uncontrolled
optimization software
Mathematik
Mathematical programming methods [See also 90Cxx]
Mixed integer programming
Combinatorial optimization
Mathematical Optimization
Berthold, Timo
Heinz, Stefan
https://opus4.kobv.de/opus4-zib/files/1067/ZR_08_12.pdf
https://opus4.kobv.de/opus4-zib/files/1067/ZR_08_12.orig.Vers.pdf
https://opus4.kobv.de/opus4-zib/files/1067/ZR_08_12.ps
https://opus4.kobv.de/opus4-zib/files/1067/ZR_08_12.orig.Vers.ps
1070
eng
reportzib
0
2008-03-25
2008-03-25
--
Models for Fare Planning in Public Transport
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.
08-16
1438-0064
1099
10.1016/j.dam.2012.02.027
urn:nbn:de:0297-zib-10708
A rev. vers. appeared in: Discrete Applied Mathematics Volume 160, Issue 18, December 2012, Pages 2591–2605
Ralf Borndörfer
unknown unknown
Marika Neumann
Marc Pfetsch
ZIB-Report
08-16
deu
uncontrolled
Preisplanung
deu
uncontrolled
Nachfragefunktion
deu
uncontrolled
Optimierung
deu
uncontrolled
Nahverkehr
Mathematik
Traffic problems
Models of real-world systems
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/1070/ZR_08_16.pdf
https://opus4.kobv.de/opus4-zib/files/1070/ZR_08_16_revised.pdf
812
eng
reportzib
0
2004-08-23
2004-08-23
--
Computing Optimal Morse Matchings
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.
04-37
813
urn:nbn:de:0297-zib-8120
Appeared in: SIAM J. Discrete Mathematics 20 (2006) 11-25
Michael Joswig
Marc Pfetsch
ZIB-Report
04-37
eng
uncontrolled
discrete Morse function
eng
uncontrolled
Morse matching
Informatik, Informationswissenschaft, allgemeine Werke
Combinatorics of partially ordered sets
None of the above, but in this section
General topology of complexes
Combinatorial optimization
ZIB Allgemein
MorseFunctions
https://opus4.kobv.de/opus4-zib/files/812/ZR-04-37.ps
https://opus4.kobv.de/opus4-zib/files/812/ZR-04-37.pdf
942
eng
reportzib
0
2006-11-17
2006-11-17
--
Orbitopal Fixing
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.
06-48
942
urn:nbn:de:0297-zib-9422
Appeared in: Proc. of the 12th Integer Programming and Combinatorial Optimization Conference (IPCO) M. Fischetti and D. Williamson (eds.), LNCS 4513, Springer-Verlag, 74-88
Volker Kaibel
Matthias Peinhardt
Marc Pfetsch
ZIB-Report
06-48
eng
uncontrolled
symmetry breaking
eng
uncontrolled
variable fixing
eng
uncontrolled
orbitopes
Informatik, Informationswissenschaft, allgemeine Werke
Special polytopes (linear programming, centrally symmetric, etc.)
Integer programming
Polyhedral combinatorics, branch-and-bound, branch-and-cut
ZIB Allgemein
MATHEON-B12:IPSym
https://opus4.kobv.de/opus4-zib/files/942/ZR_06_48.pdf
https://opus4.kobv.de/opus4-zib/files/942/ZR-06-48.pdf
https://opus4.kobv.de/opus4-zib/files/942/ZR_06_48.ps
https://opus4.kobv.de/opus4-zib/files/942/ZR-06-48.ps
948
eng
reportzib
0
2007-03-06
2007-03-06
--
Exact and Approximate Sparse Solutions of Underdetermined Linear Equations
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.
07-05
948
urn:nbn:de:0297-zib-9488
Appeared in: Applied Numerical Mathematics 60, No. 4 (2010), 452-472
Sadegh Jokar
Marc Pfetsch
ZIB-Report
07-05
eng
uncontrolled
sparse representations
eng
uncontrolled
basis pursuit
eng
uncontrolled
orthogonal matching pursuit
eng
uncontrolled
maximum feasible subsystem problem
Informatik, Informationswissenschaft, allgemeine Werke
Combinatorial optimization
Approximation methods and heuristics
ZIB Allgemein
ZIB-Infeas
https://opus4.kobv.de/opus4-zib/files/948/ZR-07-05.pdf
https://opus4.kobv.de/opus4-zib/files/948/ZR-07-05.ps
852
eng
reportzib
0
2005-03-17
2005-03-17
--
A Column-Generation Approach to Line Planning in Public Transport
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.
05-18
852
/10.1287/trsc.1060.0161
urn:nbn:de:0297-zib-8522
Appeared in: Transportation Science 41 (2007) 123-132
Ralf Borndörfer
Martin Grötschel
Marc Pfetsch
ZIB-Report
05-18
eng
uncontrolled
line planning
eng
uncontrolled
column generation
Informatik, Informationswissenschaft, allgemeine Werke
Transportation, logistics
Combinatorial optimization
ZIB Allgemein
Borndörfer, Ralf
Grötschel, Martin
MATHEON-B1
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/852/ZR-05-18.pdf
https://opus4.kobv.de/opus4-zib/files/852/ZR_05_18.orig.Vers.pdf
https://opus4.kobv.de/opus4-zib/files/852/ZR-05-18.ps
https://opus4.kobv.de/opus4-zib/files/852/ZR_05_18.orig.Vers.ps
854
eng
reportzib
0
2005-03-23
2005-03-23
--
Fare Planning for Public Transport
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.
05-20
854
urn:nbn:de:0297-zib-8541
Ralf Borndörfer
Marika Neumann
Marc Pfetsch
ZIB-Report
05-20
eng
uncontrolled
fare planning
eng
uncontrolled
demand function
eng
uncontrolled
discrete choice model
Informatik, Informationswissenschaft, allgemeine Werke
Traffic problems
Models of real-world systems
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B1
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/854/ZR-05-20.pdf
https://opus4.kobv.de/opus4-zib/files/854/ZR-05-20.ps
856
eng
reportzib
0
2005-03-23
2005-03-23
--
Public Transport to the fORe!
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?.
05-22
856
urn:nbn:de:0297-zib-8562
http://www.lionhrtpub.com/orms/orms-4-06/frtransport.html
Appeared in: OR/MS Today, Apr 2006, Vol 33 (2), 30-40
Ralf Borndörfer
Martin Grötschel
Marc Pfetsch
ZIB-Report
05-22
eng
uncontrolled
Public transport
eng
uncontrolled
vehicle scheduling
eng
uncontrolled
duty scheduling
Informatik, Informationswissenschaft, allgemeine Werke
Traffic problems
ZIB Allgemein
Borndörfer, Ralf
Grötschel, Martin
MATHEON-B1
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/856/ZR-05-22.pdf
https://opus4.kobv.de/opus4-zib/files/856/ZR-05-22.ps
910
eng
reportzib
0
2006-03-28
2006-03-28
--
Packing and Partitioning Orbitopes
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.
06-17
911
urn:nbn:de:0297-zib-9104
Appeared in: Mathematical Programming 114 (2008) 1-36
Volker Kaibel
Marc Pfetsch
ZIB-Report
06-17
eng
uncontrolled
integer programming
eng
uncontrolled
symmetry breaking
eng
uncontrolled
lexicographic representatives
Informatik, Informationswissenschaft, allgemeine Werke
Special polytopes (linear programming, centrally symmetric, etc.)
Integer programming
Polyhedral combinatorics, branch-and-bound, branch-and-cut
ZIB Allgemein
MATHEON-B12:IPSym
https://opus4.kobv.de/opus4-zib/files/910/ZR-06-17.pdf
https://opus4.kobv.de/opus4-zib/files/910/ZR-06-17.ps
2870
2008
2008
eng
conferenceobject
FGSV Verlag
0
--
--
--
Angebotsplanung im öffentlichen Nahverkehr
HEUREKA’08
http://opus.kobv.de/zib/volltexte/2008/1084/
urn:nbn:de:0297-zib-10555
Ralf Borndörfer
Marika Neumann
Marc Pfetsch
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
2856
2006
2006
eng
30
40
article
0
--
--
--
Public transport to the fORe
OR/MS Today
http://www.lionhrtpub.com/orms/orms-4-06/frtransport.html
urn:nbn:de:0297-zib-8562
Ralf Borndörfer
Martin Grötschel
Marc Pfetsch
Mathematical Optimization
Borndörfer, Ralf
Grötschel, Martin
MATHEON-B1
MATHEON-B15
2858
2006
2006
eng
405
410
conferenceobject
Springer-Verlag
0
--
--
--
Routing in Line Planning for Public Transportation
Operations Research Proceedings 2005
http://opus.kobv.de/zib/volltexte/2005/870/
urn:nbn:de:0297-zib-8706
Marc Pfetsch
Hans-Dietrich Haasis
Ralf Borndörfer
Mathematical Optimization
Borndörfer, Ralf
MATHEON-B1
MATHEON-B15
2866
2008
2008
eng
363
378
600
conferenceobject
Springer-Verlag
0
--
--
--
Models for Line Planning in Public Transport
Computer-aided Systems in Public Transport (CASPT 2004)
10.1007/978-3-540-73312-6_18
Lecture Notes in Economics and Mathematical Systems
urn:nbn:de:0297-zib-7854
Ralf Borndörfer
Mark Hickman
Martin Grötschel
Pitu Mirchandani
Marc Pfetsch
Stefan Voß
Borndörfer, Ralf
Grötschel, Martin
MATHEON-B1
MATHEON-B15
2881
2009
2009
eng
557
562
conferenceobject
Springer-Verlag
0
--
--
--
The Line Connectivity Problem
Operations Research Proceedings 2008
http://opus.kobv.de/zib/volltexte/2008/1117/
urn:nbn:de:0297-zib-10820
yes
Ralf Borndörfer
Bernhard Fleischmann
Marika Neumann
Karl Borgwardt
Marc Pfetsch
Robert Klein
Axel Tuma
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
2821
2009
2009
eng
441
446
5584
conferenceobject
Springer
0
--
--
--
Nonlinear pseudo-Boolean optimization
Theory and Applications of Satisfiability Testing – SAT 2009
Lecture Notes in Computer Science
urn:nbn:de:0297-zib-11232
yes
Timo Berthold
Oliver Kullmann
Stefan Heinz
Marc Pfetsch
Mathematical Optimization
Mathematical Optimization Methods
Berthold, Timo
Heinz, Stefan
2822
2009
2009
eng
433
438
conferenceobject
Springer-Verlag
0
--
--
--
Detecting Orbitopal Symmetries
Operations Research Proceedings 2008
urn:nbn:de:0297-zib-10842
yes
Timo Berthold
Bernhard Fleischmann
Marc Pfetsch
Karl Borgwardt
Robert Klein
Axel Tuma
Mathematical Optimization
Mathematical Optimization Methods
Berthold, Timo
3174
2007
2007
eng
123
132
1
41
article
0
--
--
--
A Column-Generation Approach to Line Planning in Public Transport
Transportation Science (INFORMS)
10.1287/trsc.1060.0161
urn:nbn:de:0297-zib-8522
Ralf Borndörfer
Martin Grötschel
Marc Pfetsch
Borndörfer, Ralf
Grötschel, Martin
MATHEON-B1
MATHEON-B15
3228
2006
2006
eng
29
36
bookpart
Springer-Verlag
0
--
--
--
Optimal Fares for Public Transport
Operations Research Proceedings 2005
{http://opus.kobv.de/zib/volltexte/2005/869/}
urn:nbn:de:0297-zib-8698
Ralf Borndörfer
Hans-Dietrich Haasis
Marika Neumann
Herbert Kopfer
Marc Pfetsch
Jörn Schönberger
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B1
MATHEON-B15
3234
2009
2009
eng
09261
conferenceobject
Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany
Dagstuhl, Germany
0
--
--
--
Line Planning and Connectivity
Models and Algorithms for Optimization in Logistics
Dagstuhl Seminar Proceedings
yes
Ralf Borndörfer
Cynthia Barnhart
Marika Neumann
Uwe Clausen
Marc Pfetsch
Ulrich Lauther
Rolf Möhring
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
6629
eng
reportzib
0
--
2017-12-21
--
The SCIP Optimization Suite 5.0
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.
1438-0064
urn:nbn:de:0297-zib-66297
Ambros Gleixner
Gregor Hendel
Leon Eifler
Tristan Gally
Gerald Gamrath
Patrick Gemander
Robert Lion Gottwald
Gregor Hendel
Christopher Hojny
Thorsten Koch
Matthias Miltenberger
Benjamin Müller
Marc Pfetsch
Christian Puchert
Daniel Rehfeldt
Franziska Schlösser
Felipe Serrano
Yuji Shinano
Jan Merlin Viernickel
Stefan Vigerske
Dieter Weninger
Jonas T. Witt
Jakob Witzig
ZIB-Report
17-61
eng
uncontrolled
constraint integer programming
eng
uncontrolled
linear programming
eng
uncontrolled
mixed-integer linear programming
eng
uncontrolled
mixed-integer nonlinear programming
eng
uncontrolled
optimization solver
eng
uncontrolled
branch-and-cut
eng
uncontrolled
branch-and-price
eng
uncontrolled
column generation framework
eng
uncontrolled
parallelization
eng
uncontrolled
mixed-integer semidefinite programming
eng
uncontrolled
Steiner tree optimization
NUMERICAL ANALYSIS
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Mathematical Optimization
Mathematical Optimization Methods
Gamrath, Gerald
Gleixner, Ambros
Gottwald, Robert
Hendel, Gregor
Koch, Thorsten
Miltenberger, Matthias
Rehfeldt, Daniel
Serrano, Felipe
Shinano, Yuji
Vigerske, Stefan
Witzig, Jakob
Müller, Benjamin
ASTfSCM
MIP-ZIBOPT
MODAL-SynLab
Siemens
Eifler, Leon
MODAL-Gesamt
Schlösser, Franziska
https://opus4.kobv.de/opus4-zib/files/6629/scipopt-50.pdf
5081
2015
eng
xvi + 376 pages
book
SIAM
0
--
--
--
Evaluating Gas Network Capacities
978-1-611973-68-6
MOS-SIAM Series on Optimization
yes
Bettina Kasse
Thorsten Koch
Benjamin Hiller
Marc Pfetsch
Lars Schewe
Mathematical Optimization
Hiller, Benjamin
Koch, Thorsten
MODAL-GasLab
ForNe
TRR154-A04
MODAL-Gesamt
4839
2013
eng
133
167
1
142
article
0
--
--
--
The Steiner connectivity problem
Mathematical Programming A
10.1007/s10107-012-0564-5
yes
urn:nbn:de:0297-zib-11171
Ralf Borndörfer
Marika Karbstein
Marika Karbstein
Marc Pfetsch
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
4860
2012
eng
2591
2605
18
160
article
0
--
--
--
Models for Fare Planning in Public Transport
Discrete Applied Mathematics
10.1016/j.dam.2012.02.027
yes
urn:nbn:de:0297-zib-10708
Ralf Borndörfer
Marika Karbstein
Marika Karbstein
Marc Pfetsch
Mathematical Optimization
Mathematics of Transportation and Logistics
Borndörfer, Ralf
MATHEON-B15
4767
2011
eng
51
60
conferenceobject
0
--
--
--
Large Neighborhood Search beyond MIP
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.
Proceedings of the 9th Metaheuristics International Conference (MIC 2011)
978-88-900984-3-7
yes
urn:nbn:de:0297-zib-12989
Timo Berthold
Engel
Stefan Heinz
Marc Pfetsch
Stefan Vigerske
Mathematical Optimization
Berthold, Timo
Heinz, Stefan
Vigerske, Stefan
5143
2013
eng
483
506
incollection
Springer
0
--
--
--
Progress in Academic Computational Integer Programming
Facets of Combinatorial Optimization
10.1007/978-3-642-38189-8_19
yes
Thorsten Koch
Michael Jünger
Bettina Kasse
Alexander Martin
Gerhard Reinelt
Marc Pfetsch
Mathematical Optimization
Koch, Thorsten
6217
eng
reportzib
0
--
2017-08-03
--
The SCIP Optimization Suite 4.0
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.
1438-0064
urn:nbn:de:0297-zib-62170
Stephen J. Maher
Ambros Gleixner
Tobias Fischer
Tristan Gally
Gerald Gamrath
Ambros Gleixner
Robert Lion Gottwald
Gregor Hendel
Thorsten Koch
Marco Lübbecke
Matthias Miltenberger
Benjamin Müller
Marc Pfetsch
Christian Puchert
Daniel Rehfeldt
Sebastian Schenker
Robert Schwarz
Felipe Serrano
Yuji Shinano
Dieter Weninger
Jonas T. Witt
Jakob Witzig
ZIB-Report
17-12
Computer aspects of numerical algorithms
Linear programming
Mixed integer programming
Nonconvex programming, global optimization
Mathematical Optimization
Mathematical Optimization Methods
Gamrath, Gerald
Gleixner, Ambros
Gottwald, Robert
Hendel, Gregor
Koch, Thorsten
Miltenberger, Matthias
Rehfeldt, Daniel
Serrano, Felipe
Shinano, Yuji
Witzig, Jakob
Maher, Stephan
Müller, Benjamin
ASTfSCM
MIP-ZIBOPT
MODAL-SynLab
Siemens
MODAL-Gesamt
https://opus4.kobv.de/opus4-zib/files/6217/scipoptsuite-40.pdf
https://opus4.kobv.de/opus4-zib/files/6217/scipoptsuite-401.pdf
5767
eng
reportzib
0
--
2016-02-26
--
The SCIP Optimization Suite 3.2
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.
1438-0064
urn:nbn:de:0297-zib-57675
no
Gerald Gamrath
Gerald Gamrath
Tobias Fischer
Tristan Gally
Ambros Gleixner
Gregor Hendel
Thorsten Koch
Stephen J. Maher
Matthias Miltenberger
Benjamin Müller
Marc Pfetsch
Christian Puchert
Daniel Rehfeldt
Sebastian Schenker
Robert Schwarz
Felipe Serrano
Yuji Shinano
Stefan Vigerske
Dieter Weninger
Michael Winkler
Jonas T. Witt
Jakob Witzig
ZIB-Report
15-60
eng
uncontrolled
mixed-integer linear and nonlinear programming
eng
uncontrolled
MIP solver
eng
uncontrolled
MINLP solver
eng
uncontrolled
linear programming
eng
uncontrolled
LP solver
eng
uncontrolled
simplex method
eng
uncontrolled
modeling
eng
uncontrolled
parallel branch-and-bound
eng
uncontrolled
branch-cut-and-price framework
eng
uncontrolled
generic column generation
eng
uncontrolled
Steiner tree solver
eng
uncontrolled
multi-criteria optimization
eng
uncontrolled
mixed-integer semidefinite programming
Parallel computation
Linear programming
Integer programming
Mixed integer programming
Nonlinear programming
Applications of mathematical programming
Mathematical Optimization
Mathematical Optimization Methods
Gamrath, Gerald
Gleixner, Ambros
Hendel, Gregor
Koch, Thorsten
Miltenberger, Matthias
Rehfeldt, Daniel
Serrano, Felipe
Shinano, Yuji
Vigerske, Stefan
Winkler, Michael
Witzig, Jakob
Maher, Stephan
Müller, Benjamin
ASTfSCM
MIP-ZIBOPT
MODAL-SynLab
CRC1026
Siemens
MODAL-Gesamt
https://opus4.kobv.de/opus4-zib/files/5767/scipopt-32.pdf
1512
deu
reportzib
0
2012-04-19
2012-04-19
--
Optimierung Technischer Kapazitäten in Gasnetzen
Die mittel- und längerfristige Planung für den Gastransport hat sich durch
Änderungen 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 Kapazität und Topologieplanung bezeichnet werden. Diese
mathematischen Optimierungsprobleme werden vorgestellt und Lösungsansätze
skizziert.
1438-0064
urn:nbn:de:0297-zib-15121
Alexander Martin
Benjamin Hiller
Björn Geißler
Christine Hayn
Benjamin Hiller
Jesco Humpola
Thorsten Koch
Thomas Lehmann
Antonio Morsi
Marc Pfetsch
Lars Schewe
Martin Schmidt
Rüdiger Schultz
Robert Schwarz
Jonas Schweiger
Marc Steinbach
Bernhard Willert
ZIB-Report
11-56
deu
uncontrolled
Gasnetzplanung
deu
uncontrolled
Technische Kapazitäten
deu
uncontrolled
Nominierungsvalidierung
deu
uncontrolled
Buchungsvalidierung
deu
uncontrolled
Topologieplanung
Computer Applications
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Mathematical Optimization
Hiller, Benjamin
Koch, Thorsten
MODAL-GasLab
ForNe
MODAL-Gesamt
Schweiger, Jonas
https://opus4.kobv.de/opus4-zib/files/1512/ZR-11-56.pdf
5795
2015
eng
article
0
2015-11-25
--
--
GasLib - A Library of Gas Network Instances
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.
Optimization Online
urn:nbn:de:0297-zib-57950
no
http://www.optimization-online.org/DB_FILE/2015/11/5216.pdf
Jesco Humpola
Robert Schwarz
Imke Joormann
Djamal Oucherif
Marc Pfetsch
Lars Schewe
Martin Schmidt
Robert Schwarz
Mathematical Optimization
MODAL-GasLab
ForNe
MODAL-Gesamt
https://opus4.kobv.de/opus4-zib/files/5795/humpola2015gaslib.pdf
3267
2011
2011
eng
105
114
conferenceobject
VDI-Verlag, Düsseldorf
0
--
--
--
Optimierung Technischer Kapazitäten in Gasnetzen
Optimierung in der Energiewirtschaft
VDI-Berichte 2157
urn:nbn:de:0297-zib-15121
no
Alexander Martin
Björn Geißler
Christine Heyn
Benjamin Hiller
Jesco Humpola
Thorsten Koch
Thomas Lehmann
Antonio Morsi
Marc Pfetsch
Lars Schewe
Martin Schmidt
Rüdiger Schultz
Robert Schwarz
Jonas Schweiger
Marc Steinbach
Bernhard Willert
Mathematical Optimization
Hiller, Benjamin
Koch, Thorsten
MODAL-GasLab
ForNe
MODAL-Gesamt
Schweiger, Jonas
6588
2017
eng
4
2
article
0
--
--
--
GasLib – A Library of Gas Network Instances
Data
10.3390/data2040040
no
Martin Schmidt
Regine Kossick
Denis Assmann
Robert Burlacu
Jesco Humpola
Imke Joormann
Nikolaos Kanelakis
Thorsten Koch
Djamal Oucherif
Marc Pfetsch
Lars Schewe
Robert Schwarz
Matthias Sirvent
Mathematical Optimization
Koch, Thorsten
MODAL-GasLab
TRR154-A04
MODAL-Gesamt
6936
eng
reportzib
0
--
2018-07-02
--
The SCIP Optimization Suite 6.0
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.
1438-0064
urn:nbn:de:0297-zib-69361
Matthias Miltenberger
Ambros Gleixner
Michael Bastubbe
Leon Eifler
Tristan Gally
Gerald Gamrath
Robert Lion Gottwald
Gregor Hendel
Christopher Hojny
Thorsten Koch
Marco Lübbecke
Stephen J. Maher
Matthias Miltenberger
Benjamin Müller
Marc Pfetsch
Christian Puchert
Daniel Rehfeldt
Franziska Schlösser
Christoph Schubert
Felipe Serrano
Yuji Shinano
Jan Merlin Viernickel
Matthias Walter
Fabian Wegscheider
Jonas T. Witt
Jakob Witzig
ZIB-Report
18-26
eng
uncontrolled
constraint integer programming
eng
uncontrolled
linear programming
eng
uncontrolled
mixed-integer linear programming
eng
uncontrolled
mixed-integer nonlinear programming
eng
uncontrolled
optimization solver
eng
uncontrolled
branch-and-cut
eng
uncontrolled
branch-and-price
eng
uncontrolled
column generation framework
eng
uncontrolled
parallelization
eng
uncontrolled
mixed-integer semidefinite programming
eng
uncontrolled
Steiner tree optimization
NUMERICAL ANALYSIS
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Mathematical Optimization
Mathematical Optimization Methods
Gamrath, Gerald
Gleixner, Ambros
Gottwald, Robert
Hendel, Gregor
Koch, Thorsten
Miltenberger, Matthias
Rehfeldt, Daniel
Serrano, Felipe
Shinano, Yuji
Vigerske, Stefan
Witzig, Jakob
Müller, Benjamin
ASTfSCM
MIP-ZIBOPT
MODAL-SynLab
Siemens
Eifler, Leon
MODAL-Gesamt
Schlösser, Franziska
Plan4res
https://opus4.kobv.de/opus4-zib/files/6936/scipopt-60.pdf
7679
2018
eng
1
25
25
27
article
0
--
--
--
Solving MIPs via Scaling-based Augmentation
Discrete Optimization
1509.03206
Additional Note: doi: 10.1016/j.disopt.2017.08.004
URL of the PDF: http://dx.doi.org/10.1016/j.disopt.2017.08.004
@article{BPPP2015, Annote = {doi: 10.1016/j.disopt.2017.08.004}, Arxiv = {http://arxiv.org/abs/1509.03206}, Author = {Le~Bodic, P. and Pfetsch, M. and Pavelka, J. and Pokutta, S.}, Date-Added = {2020-01-16 11:23:36 +0100}, Date-Modified = {2020-01-16 11:23:36 +0100}, Journal = {{Discrete Optimization}}, Pages = {1--25}, Pdfurl = {http://dx.doi.org/10.1016/j.disopt.2017.08.004}, Ptype = {journal}, Title = {{Solving MIPs via Scaling-based Augmentation}}, Volume = {27}, Year = {2018}}
06d457253b056bd3d95724ce1a400f6c
2020-01-31T11:11:00+00:00
pubPokutta.bib
bibtex
5e340b4467c4b8.55545756
false
true
P. Le Bodic
Marc Pfetsch
J. Pavelka
Sebastian Pokutta
no-project
Pokutta, Sebastian
7814
eng
reportzib
0
--
2020-04-03
--
Estimating the Size of Branch-And-Bound Trees
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.
1438-0064
urn:nbn:de:0297-zib-78144
Gregor Hendel
Gregor Hendel
Daniel Anderson
Pierre Le Bodic
Marc Pfetsch
ZIB-Report
20-02
eng
uncontrolled
mixed integer programming
eng
uncontrolled
machine learning
eng
uncontrolled
branch and bound
eng
uncontrolled
forecasting
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Mathematical Optimization
Hendel, Gregor
ASTfSCM
MODAL-SynLab
Siemens
MODAL-Gesamt
https://opus4.kobv.de/opus4-zib/files/7814/zibreportestimatingSearchTreeSize.pdf
7802
eng
reportzib
0
--
2020-03-30
--
The SCIP Optimization Suite 7.0
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.
1438-0064
urn:nbn:de:0297-zib-78023
false
true
Gerald Gamrath
Felipe Serrano
Daniel Anderson
Ksenia Bestuzheva
Wei-Kun Chen
Leon Eifler
Maxime Gasse
Patrick Gemander
Ambros Gleixner
Leona Gottwald
Katrin Halbig
Gregor Hendel
Christopher Hojny
Thorsten Koch
Pierre Le Bodic
Stephen J. Maher
Frederic Matter
Matthias Miltenberger
Erik Mühmer
Benjamin Müller
Marc Pfetsch
Franziska Schlösser
Felipe Serrano
Yuji Shinano
Christine Tawfik
Stefan Vigerske
Fabian Wegscheider
Dieter Weninger
Jakob Witzig
ZIB-Report
20-10
NUMERICAL ANALYSIS
OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
Mathematical Optimization
Mathematical Optimization Methods
Gamrath, Gerald
Gleixner, Ambros
Gottwald, Robert
Hendel, Gregor
Koch, Thorsten
Miltenberger, Matthias
Serrano, Felipe
Shinano, Yuji
Vigerske, Stefan
Witzig, Jakob
Maher, Stephan
Müller, Benjamin
ASTfSCM
MIP-ZIBOPT
MODAL-SynLab
Siemens
Eifler, Leon
MODAL-Gesamt
Schlösser, Franziska
Bestuzheva, Ksenia
Tawfik, Christine
Plan4res
https://opus4.kobv.de/opus4-zib/files/7802/scipopt-70.pdf
1086
eng
reportzib
ZIB
EPN Quito
0
2008-08-19
2008-08-19
--
Line Planning on Paths and Tree Networks with Applications to the Quito Trolebus System
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.
08-35
1438-0064
1120
urn:nbn:de:0297-zib-10869
Appeared in: ATMOS 2008 - 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems. Matteo Fischetti and Peter Widmayer (eds.) Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 2008
Luis Miguel Torres
unknown unknown
Ramiro Torres
Ralf Borndörfer
Marc Pfetsch
ZIB-Report
08-35
eng
uncontrolled
line planning
eng
uncontrolled
computational complexity
eng
uncontrolled
public transport
eng
uncontrolled
integer programming
Mathematik
Transportation, logistics
Combinatorial optimization
Mathematical Optimization
Borndörfer, Ralf
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/1086/ZR_08_35.pdf
https://opus4.kobv.de/opus4-zib/files/1086/ZR_08_35.ps
1107
eng
reportzib
0
2008-12-18
2008-12-18
--
Line Planning on Paths and Tree Networks with Applications to the Quito Trolebus System (Extended 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.
08-53
1438-0064
1148
urn:nbn:de:0297-zib-11076
Appeared in: ATMOS 2008 - 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems. Matteo Fischetti and Peter Widmayer (eds.)Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany, Dagstuhl, Germany, 2008. http://drops.dagstuhl.de/opus/volltexte/2008/1583
Luis Miguel Torres
unknown unknown
Ramiro Torres
Ralf Borndörfer
Marc Pfetsch
ZIB-Report
08-53
eng
uncontrolled
line planning
eng
uncontrolled
computational complexity
eng
uncontrolled
public transport
eng
uncontrolled
integer programming
Mathematik
Combinatorial optimization
Mathematical Optimization
Borndörfer, Ralf
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/1107/ZR_08_53.pdf
https://opus4.kobv.de/opus4-zib/files/1107/ZR_08_53.ps
1106
eng
reportzib
0
2008-12-18
2008-12-18
--
On the Line Planning Problem in Tree Networks
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.
08-52
1438-0064
1147
urn:nbn:de:0297-zib-11069
Luis Miguel Torres
unknown unknown
Ramiro Torres
Ralf Borndörfer
Marc Pfetsch
ZIB-Report
08-52
eng
uncontrolled
line planning
eng
uncontrolled
computational complexity
eng
uncontrolled
public transport optimization
Mathematik
Combinatorial optimization
Mathematical Optimization
Borndörfer, Ralf
MATHEON-B1
MATHEON-B15
https://opus4.kobv.de/opus4-zib/files/1106/ZR_08_52.pdf
https://opus4.kobv.de/opus4-zib/files/1106/ZR_08_52.ps
2874
2008
2008
eng
conferenceobject
Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany
Dagstuhl, Germany
0
--
--
--
Line Planning on Paths and Tree Networks with Applications to the Quito Trolebus System
ATMOS 2008 - 8th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems
http://drops.dagstuhl.de/opus/volltexte/2008/1580
urn:nbn:de:0297-zib-10869
Luis Miguel Torres
Matteo Fischetti
Ramiro Torres
Peter Widmayer
Ralf Borndörfer
Marc Pfetsch
Mathematical Optimization
Borndörfer, Ralf
MATHEON-B15
8073
2020
eng
article
0
--
--
--
Capacity Evaluation for Large-Scale Gas Networks
German Success Stories
no
2020
Thorsten Koch
Martin Schmidt
Benjamin Hiller
Marc Pfetsch
Björn Geißler
René Henrion
Imke Joormann
Alexander Martin
Antonio Morsi
Werner Römisch
Lars Schewe
Rüdiger Schultz
Hiller, Benjamin
Koch, Thorsten
MODAL-Gesamt
Mathematical Algorithmic Intelligence
Applied Algorithmic Intelligence Methods
MODAL-EnergyLab
8049
2020
eng
conferenceobject
0
--
--
--
IPBoost – Non-Convex Boosting via Integer Programming
Proceedings of ICML
2002.04679
URL of the Code: https://www2.mathematik.tu-darmstadt.de/~pfetsch/ipboost.html
URL of the Slides: https://app.box.com/s/8dpvmls88suouy11bkpwufhu7iiz6dxl
URL of the Abstract: http://www.pokutta.com/blog/research/2020/02/13/ipboost-abstract.html
@article{PP2020, acceptnotice = {{There were 4990 papers reviewed for ICML this year, of which the program committee accepted 1088 for presentation. You can access the reviews and meta-review of your paper by logging in to the author console at https://cmt3.research.microsoft.com/ICML2020/}}, acceptrate = {21.8}, arxiv = {https://arxiv.org/abs/2002.04679}, author = {Pfetsch, M. and Pokutta, S.}, code = {https://www2.mathematik.tu-darmstadt.de/~pfetsch/ipboost.html}, date-added = {2020-11-22 13:04:18 +0100}, date-modified = {2020-11-22 13:04:30 +0100}, journal = {{Proceedings of ICML}}, ptype = {conference}, slides = {https://app.box.com/s/8dpvmls88suouy11bkpwufhu7iiz6dxl}, summary = {http://www.pokutta.com/blog/research/2020/02/13/ipboost-abstract.html}, title = {{IPBoost -- Non-Convex Boosting via Integer Programming}}, year = {2020}}
04c8ce2b4afd11477caa214926057bda
2020-11-24T09:22:24+00:00
pokutta-2020.bib
bibtex
5fbcd0d091bac7.18675871
yes
Marc Pfetsch
Sebastian Pokutta
no-project
Pokutta, Sebastian
Mathematical Algorithmic Intelligence
AI in Society, Science, and Technology
1653
eng
reportzib
0
2012-11-19
2012-11-19
--
Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions
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.
1438-0064
urn:nbn:de:0297-zib-16531
10.1080/10556788.2014.888426
Appeared in: Optimization Methods and Software 30 (2015) pp. 15-53
Marc Pfetsch
Jonas Schweiger
Armin Fügenschuh
Björn Geißler
Nina Geißler
Ralf Gollmer
Benjamin Hiller
Jesco Humpola
Thorsten Koch
Thomas Lehmann
Alexander Martin
Antonio Morsi
Jessica Rövekamp
Lars Schewe
Martin Schmidt
Rüdiger Schultz
Robert Schwarz
Jonas Schweiger
Claudia Stangl
Marc Steinbach
Stefan Vigerske
Bernhard Willert
ZIB-Report
12-41
Software
Computer Applications
Computational methods
Mixed integer programming
Nonlinear programming
Applications of mathematical programming
Mathematical Optimization
Fügenschuh, Armin
Hiller, Benjamin
Koch, Thorsten
Vigerske, Stefan
MODAL-GasLab
ForNe
MODAL-Gesamt
Schweiger, Jonas
https://opus4.kobv.de/opus4-zib/files/1653/ZR-12-41.pdf
https://opus4.kobv.de/opus4-zib/files/1653/ZR-12-41_revised.pdf
4718
2014
eng
article
Taylor & Francis
0
--
--
--
Validation of Nominations in Gas Network Optimization: Models, Methods, and Solutions
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.
Optimization Methods and Software
10.1080/10556788.2014.888426
yes
urn:nbn:de:0297-zib-16531
Robert Schwarz
Marc Pfetsch
Armin Fügenschuh
Björn Geißler
Nina Geißler
Ralf Gollmer
Benjamin Hiller
Jesco Humpola
Thorsten Koch
Thomas Lehmann
Alexander Martin
Antonio Morsi
Jessica Rövekamp
Lars Schewe
Martin Schmidt
Rüdiger Schultz
Robert Schwarz
Jonas Schweiger
Claudia Stangl
Marc Steinbach
Stefan Vigerske
Bernhard Willert
Mathematical Optimization
Fügenschuh, Armin
Hiller, Benjamin
Koch, Thorsten
Vigerske, Stefan
Schweiger, Jonas
5349
2015
eng
SIAM-MOS series on Optimization
bookpart
0
--
--
--
Computational results for validation of nominations
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.
Evaluating Gas Network Capacities
9781611973686
yes
Benjamin Hiller
Jesco Humpola
Jesco Humpola
Thomas Lehmann
Ralf Lenz
Antonio Morsi
Marc Pfetsch
Lars Schewe
Martin Schmidt
Robert Schwarz
Jonas Schweiger
Claudia Stangl
Bernhard Willert
Mathematical Optimization
Hiller, Benjamin
Lenz, Ralf
MODAL-GasLab
ForNe
TRR154-A04
MODAL-Gesamt
Schweiger, Jonas
5877
2015
eng
3
16
bookpart
Society for Industrial and Applied Mathematics
0
--
--
--
Introduction
Evaluating Gas Network Capacities
9781611973686
SIAM-MOS series on Optimization
yes
Thorsten Koch
Janina Zittel
Marc Pfetsch
Jessica Rövekamp
Mathematical Optimization
Koch, Thorsten
MODAL-GasLab
ForNe
MODAL-Gesamt
5878
2015
eng
65
84
bookpart
Society for Industrial and Applied Mathematics
0
--
--
--
State-of-the-art in evaluating gas network capacities
Evaluating Gas Network Capacities
9781611973686
SIAM-MOS series on Optimization
yes
Dagmar Bargmann
Janina Zittel
Mirko Ebbers
Nina Heinecke
Thorsten Koch
Veronika Kühl
Antje Pelzer
Marc Pfetsch
Jessica Rövekamp
Klaus Spreckelsen
Mathematical Optimization
Koch, Thorsten
MODAL-GasLab
ForNe
MODAL-Gesamt
5880
2015
eng
87
102
bookpart
Society for Industrial and Applied Mathematics
0
--
--
--
Mathematical optimization for evaluating gas network capacities
Evaluating Gas Network Capacities
9781611973686
SIAM-MOS series on Optimization
yes
Lars Schewe
Janina Zittel
Thorsten Koch
Alexander Martin
Marc Pfetsch
Mathematical Optimization
Koch, Thorsten
MODAL-GasLab
ForNe
MODAL-Gesamt