Main.Invited History

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April 01, 2012, at 09:43 PM EST by 83.200.151.211 -
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'''''Automatic Decomposition and Branch-and-Price: A Status Report'''''

In this talk, we give an overview of our recent efforts to automatize
Dantzig-Wolfe reformulation and column generation/branch-and-price for
structured, large-scale integer programs. We present the need for and
the benefits from a generic implementation which does not need any
user interaction or expert knowledge. A focus is on detecting
structures in integer programs which are amenable to a Dantzig-Wolfe
reformulation. We give computational results and discuss future
research topics.

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'''''Continuous Local Strategies for Robotic Formation Problems'''''

We consider a scenario with a team of autonomous mobile
robots which are placed in the plane. Their goal is to move in such a way
that they eventually reach a prescribed formation. Such a formation may
be a straight line between two given endpoints (Robot Chain Problem),
a circle or any other geometric pattern, or just one point (Gathering
Problem). In this survey, we assume that there is no central control that
guides the robot's decisions, thus the robots have to self-organize in order
to accomplish global tasks like the above-mentioned formation problems.
Moreover, we restrict them to simple local strategies: the robots are limited
to "see" only robots within a bounded viewing range; their decisions
where to move next are solely based on the relative positions of robots
within this range. Most strategies for these type of problems assume a
discrete time model, i.e., time is divided into rounds, in a round, each
robot moves to some target point de ned by the observations of its environment.
In this talk, we focus on a much less examined class of local strategies,
namely continuous strategies. Here, each robot continuously observes his
environment and continuously adapts its speed and direction to these
observations. focus on these type of strategies and survey recent results
on local strategies for short robot chains and gathering in the continuous
time model. We present such strategies for the Robot Chain and the
Gathering Problem and analyze them w.r.t. the distance traveled by the
robots. For both problems, we survey bounds for the "price of locality",
namely the ratio between the cost of our local algorithms and the optimal
cost assuming global view, for each individual start con guration.

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Friedhelm Meyer auf der Heide is Full Professor in the Computer Science Department and the Heinz Nixdorf Institute at the University of Paderborn. He received his PhD in Mathematics Bielefeld and his Habilitation in Computer Science in Frankfurt. After a 2-years stay in Dortmund as an Associate Professor he moved to Paderborn in 1989. His research interests include algorithmic and complexity theoretical problems about parallel computing, communication and data management in networks, dynamics in networks, algorithmic foundations on robotic exploration and formation problems,
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Friedhelm Meyer auf der Heide is Full Professor in the Computer Science Department and the Heinz Nixdorf Institute at the University of Paderborn. He received his PhD in Mathematics in Bielefeld and his Habilitation in Computer Science in Frankfurt. After a 2-years stay in Dortmund as an Associate Professor he moved to Paderborn in 1989. His research interests include algorithmic and complexity theoretical problems about parallel computing, communication and data management in networks, dynamics in networks, algorithmic foundations on robotic exploration and formation problems,
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Friedhelm Meyer auf der Heide is Full Professor in the Computer Science Department and the Heinz Nixdorf Institute at the University of Paderborn. He received his PhD in Mathematics Bielefeld and his Habilitation in Computer Science in Frankfurt. After a 2-years stay in Dortmund as an Associate Professor he moved to Paderborn in 1989. His research interests include algorithmic and complexity theoretical problems about parallel computing, communication and data management in networks, dynamics in networks, algorithmic foundations on robotic exploration and formation problems,
algorithms in computer graphics, and probabilistic analysis, His research is described in more than 150 publications. He was the coordinator of European integrated project DELIS and the
CRC “Massively Parallel Computing”, and currently coordinates the newly founded CRC “On-The-Fly Computing”, both financed by the “Deutsche Forschungsgemeinschaft” (DFG). In 1992 he received the Leibniz research award of the DFG together with Burkhard Monien. Since 2007, he is member of the German Academy of Science LEOPOLDINA.
March 20, 2012, at 05:09 PM EST by 82.125.230.187 -
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Marco Lübbecke is a full professor for operations research at RWTH
Aachen University, Germany. He received his Ph.D. in applied
mathematics from TU Braunschweig in 2001 and held positions as
assistant professor for combinatorial optimization and graph
algorithms at TU Berlin and as visiting professor for discrete
optimization at TU Darmstadt.

Marco's research interests are in computational integer programming
and discrete optimization. A particular focus is on decomposition
approaches to exactly solving large-scale real-world optimization
problems. With his appreciation for the beauty of mathematics, and
being an editor of OR journals and PC member of algorithms
conferences, he finds that the most fascinating challenges are
interdisciplinary in nature.
March 18, 2012, at 11:30 PM EST by 82.125.230.187 -
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The talk will give an overview of our recent work on balanced graph partitioning - partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into a distributed evolutionary algorithm.
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The talk will give an overview of our recent work on balanced graph partitioning - partition the nodes of a graph into ''k'' blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into a distributed evolutionary algorithm.
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The talk will give an overview of our recent work on balanced graph partitioning - partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
to:
The talk will give an overview of our recent work on balanced graph partitioning - partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into a distributed evolutionary algorithm.
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The talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
to:
The talk will give an overview of our recent work on balanced graph partitioning - partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
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Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prizes, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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''Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.''
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Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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''Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.''
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* [[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn)
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(:cellnr align=left valign=top :)
*[[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University)
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* [[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn)
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*[[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University)
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* [[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University)
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(:cellnr align=left valign=top :)
*[[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University)
(:cell align=left valign=top :)
Attach:luebbecke.jpg

(:cellnr align=left valign=top :)
* [[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn)
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Attach:meyer-auf-der-heide.jpg

(:tableend:)
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http://algo2.iti.kit.edu/img/content/sm_sanders_5584_rdax_178x169.jpg Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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http://algo2.iti.kit.edu/img/content/sm_sanders_5584_rdax_178x169.jpg
Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
to:
http://algo2.iti.kit.edu/img/content/sm_sanders_5584_rdax_178x169.jpg Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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'''''Short Bio''''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.

'''''Title''''' ''Engineering Graph Partitioning Algorithms''

'''''Abstract'''''
The talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
to:
Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.

''Engineering Graph Partitioning Algorithms''

The
talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
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'''''Title''''' ''Engineering Graph Partitioning Algorithms''
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'''Title''' Engineering Graph Partitioning Algorithms

'''Abstract''' The talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
to:
'''''Title''''' Engineering Graph Partitioning Algorithms

'''''Abstract''''' The talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
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''''Short Bio'''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
to:
'''''Short Bio''''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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'''Short Bio''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
to:
''''Short Bio'''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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''Short Bio'' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
to:
'''Short Bio''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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'''Short Bio''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
to:
''Short Bio'' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.

Engineering Graph Partitioning Algorithms

The talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
to:
'''Short Bio''' Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.

'''Title''' Engineering Graph Partitioning Algorithms

'''Abstract''' The talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
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Engineering Graph Partitioning Algorithms

The talk will give an overview of our recent work on balanced graph partitioning -- partition the nodes of a graph into k blocks such that all blocks have approximately equal size and such that the number of cut edges is small. This problem has numerous applications for example in parallel processing. We report on a scalable parallelization and a number of improvements on the classical multi-level approach which leads to improved partitioning quality. This includes an integration of flow methods, improved local search, several improved coarsening schemes, repeated runs similar to the solutions used in multigrid solver, and an integration into an distributed evolutionary algorithm.
Overall this leads to a system that for many common benchmark instances leads to both the best quality solution known and favorable tradoffs between running time and solution quality.
March 18, 2012, at 01:22 PM EST by 82.125.230.187 -
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Peter Sanders received his PhD in computer science from Universität Karlsruhe, Germany in 1996.  After 7 years at the Max-Planck-Institute for Informatics in Saarbrücken he returned to Karlsruhe as a full professor in 2004. He has more than 170 publications, mostly on algorithms for large data sets. This includes parallel algorithms (load balancing,...) memory hierarchies, graph algorithms (route planning, graph partitioning...), randomized algorithms, full text indices,... He is very active in promoting the methodology of algorithm engineering. For example, he currently heads a DFG priority program on AE in Germany. Peter Sanders won a number of prices, perhaps most notably the DFG Leibniz Award 2012 which amounts to 2.5 million Euros of research money.
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* [[http://algo2.iti.kit.edu/english/sanders.php|Peter Sanders]] (Karlsruhe Institute of Technology)
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* [[http://algo2.iti.kit.edu/english/sanders.php|Peter Sanders]] (Karlsruhe Institute of Technology)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University) - TBA
*
[[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn) - TBA
*
[[http://algo2.iti.kit.edu/english/sanders.php|Peter Sanders]] (Karlsruhe Institute of Technology) - TBA
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University)
* [[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn)
* [[http://algo2.iti.kit.edu/english/sanders.php|Peter Sanders]] (Karlsruhe Institute of Technology)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University)
* [[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn)
* [[http://algo2.iti.kit.edu/english/sanders.php|Peter Sanders]] (Karlsruhe Institute of Technology)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University) - TBA
*
[[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn) - TBA
*
[[http://algo2.iti.kit.edu/english/sanders.php|Peter Sanders]] (Karlsruhe Institute of Technology) - TBA
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* [[http://algo2.iti.kit.edu/sanders.php|Peter Sanders]] (Karlsruhe Institute of Technology)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco Lübbecke]] (RWTH Aachen University)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco E. Lübbecke]] (RWTH Aachen University)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco Lübbecke]] (RWTH Aachen)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco Lübbecke]] (RWTH Aachen University)
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* Marco Lübbecke (RWTH Aachen)
* Friedhelm Meyer auf der Heide (University of Paderborn)
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* [[http://www.or.rwth-aachen.de/luebbecke/|Marco Lübbecke]] (RWTH Aachen)
* [[http://wwwhni.uni-paderborn.de/en/alg/staff/fmadh/|Friedhelm Meyer auf der Heide]] (University of Paderborn)
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* [[Peter Sanders|http://algo2.iti.kit.edu/sanders.php]] (Karlsruhe Institute of Technology)
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* Peter Sanders (Karlsruhe Institute of Technology)
to:
* [[Peter Sanders|http://algo2.iti.kit.edu/sanders.php]] (Karlsruhe Institute of Technology)
March 09, 2012, at 05:06 PM EST by 147.210.128.178 -
Added lines 1-3:
* Marco Lübbecke (RWTH Aachen)
* Friedhelm Meyer auf der Heide (University of Paderborn)
* Peter Sanders (Karlsruhe Institute of Technology)