Experimental Algorithms: 8th International Symposium SEA 2009, Dortmund, Germany, June 4-6, 2009, ProceedingsThis volume contains the papers presented at the 8th International Symposium on Experimental Algorithms (SEA 2009).The symposium was held at the Te- nische Universit¨ at Dortmund, Germany, during June 4–6, 2009. The main theme of the SEA series is the role of experimentation and of algorithm engineering techniques in the design and evaluation of algorithms and data structures. Contributions are supported by experimental evaluation, methodological issues in the design and interpretation of experiments, the use of (meta-)heuristics, or application-driven case studies that deepen the und- standing of a problem's complexity. For each symposium, papers are solicited from all areas of algorithmic engineering research. Previous meetings, under the name of “Workshop on Experimental Al- rithms” (WEA), were held in Riga (Latvia, 2001), Ascona (Switzerland, 2003), Angra dos Reis (Brazil, 2004), Santorini (Greece, 2005), Menorca Island (Spain, 2006), Rome (Italy, 2007), and Provincetown (USA, 2008). The ProgramCommittee ofSEA 2009received64 submissions.Eachsubm- sion was reviewed by at least three ProgramCommittee members and evaluated on its quality,originality,and relevance to the symposium. Overall,the Program Committee wrote249 reviews with the help of almost 100 trusted external ref- ees. The Committee selected 23 papers, leading to an acceptance rate of 35.9%. The decision process was made electronically using the EasyChair conference management system. In additionto the accepted contributions,this volumealso containsabstracts ofthe invitedtalks givenby Heinz Bast(Intel), MichaelA. Bender (Stony Brook ˆ University and Tokutek, Inc.), and Marc Schoenauer (INRIA Saclay – Ile-de- France). |
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Contents
Parallelism in Current and Future Processors Challenges and Support for Designing Optimal Algorithms Invited Talk | 1 |
How a Theoretician Learned to be VP of Engineering Invited Talk | 2 |
Experimental Comparisons of Derivative Free Optimization Algorithms Invited Talk | 3 |
On Computational Models for Flash Memory Devices | 16 |
Competitive Buffer Management with Stochastic Packet Arrivals | 28 |
Fast and Accurate Bounds on Linear Programs | 40 |
An Experimental Study | 51 |
A Lightweight cOriented BoundingVolume Hierarchy | 63 |
Scheduling Additional Trains on Dense Corridors | 149 |
Broadword Computing and Fibonacci Code Speed Up Compressed Suffix Arrays | 161 |
SpeedUp Techniques for the Selfish Step Algorithm in Network Congestion Games | 173 |
Experimental Study of Nonoblivious Greedy and Randomized Rounding Algorithms for Hypergraph bMatching Extended Abstract | 185 |
Empirical Evaluation of Graph Partitioning Using Spectral Embeddings and Flow | 197 |
Univariate Algebraic Kernel and Application to Arrangements | 209 |
Fast Algorithm for Graph Isomorphism Testing | 221 |
Algorithms and Experiments for Clique RelaxationsFinding Maximum sPlexes | 233 |
psort Yet Another Fast Stable Sorting Software | 76 |
A Heuristic for Fair CorrelationAware Resource Placement | 89 |
Measuring the Similarity of Geometric Graphs | 101 |
A Heuristic Strong Connectivity Algorithm for Large Graphs | 113 |
Pareto Paths with SHARC | 125 |
An Application of Selforganizing Data Structures to Compression | 137 |
A DesignforYield Algorithm to Assess and Improve the Structural and Energetic Robustness of Proteins and Drugs | 245 |
Multilevel Algorithms for Modularity Clustering | 257 |
Towards Composite Measures of Presortedness | 269 |
Computing Elevation Maxima by Searching the Gauss Sphere | 281 |
Author Index | 293 |
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Common terms and phrases
algebraic numbers approach approximation b-matching B-tree benefit Berlin Heidelberg 2009 BFGS bitsize block bounds buffer c-dop-tree c-rb-tree Calgary Corpus cgal clusters CMA-ES coefficients compression compute conauto Condition number cost data set data structure defined definition denote different disk edge weight effective efficient experimental experiments external-memory filter find first fit function graph G greedy greedy algorithm Heidelberg heuristic hypergraphs implementation input integer iteration kernel labels linear list update algorithms LNCS maximum MAXSBCC memory merge modularity multi-criteria Nash equilibrium nodes ofsize ofthe optimal OSVV packets parameter partition path computations performance player polynomials preprocessing priority queue problem protein psort queries queue random randomized rounding refinement robustness Rosenbrock function runningtime search tree Section selfish step algorithm sequence SHARC shortest path shortest path problem solution SOLVER SpecFlow spectral speed-up Springer strategy suffix theoretical traffic Tuned SWSF unit-cost flash model Vahrenhold vector vertex vertices
