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 Tobias Friedrich

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Average citations per article2.50
Citation Count50
Publication count20
Publication years2010-2017
Available for download6
Average downloads per article91.83
Downloads (cumulative)551
Downloads (12 Months)97
Downloads (6 Weeks)6
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1
February 2017 Algorithmica: Volume 77 Issue 2, February 2017
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

In this paper we initiate the study of job scheduling on related and unrelated machines so as to minimize the maximum flow time or the maximum weighted flow time (when each job has an associated weight). Previous work for these metrics considered only the setting of parallel machines, while previous ...
Keywords: Minimizing flow-time, Online algorithms, Scheduling, Competitive analysis

2
December 2015 Evolutionary Computation: Volume 23 Issue 4, Winter 2015
Publisher: MIT Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 0,   Downloads (12 Months): 10,   Downloads (Overall): 34

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Many combinatorial optimization problems have underlying goal functions that are submodular. The classical goal is to find a good solution for a given submodular function f under a given set of constraints. In this paper, we investigate the runtime of a simple single objective evolutionary algorithm called <inline-formula><inline-graphic xlink="EVCO_a_00159inline1.gif" xlink:type="simple"/></inline-formula> ...
Keywords: runtime, Submodular functions, approximation, matroid constraints, hypervolume indicator, maximum cut, multiobjective optimization, theory

3
September 2015 Journal of Discrete Algorithms: Volume 34 Issue C, September 2015
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

Covering all edges of a graph by a minimum number of cliques is a well known NP -hard problem. For the parameter k being the maximal number of cliques to be used, the problem becomes fixed parameter tractable. However, assuming the Exponential Time Hypothesis, there is no kernel of subexponential ...
Keywords: Clique cover, Random intersection graphs, Average case, Erdős-Renyi graphs, Kernelization, Parameterized algorithms

4
July 2015 ICALP 2015: Proceedings, Part II, of the 42nd International Colloquium on Automata, Languages, and Programming - Volume 9135
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

The performance of large distributed systems crucially depends on efficiently balancing their load. This has motivated a large amount of theoretical research how an imbalanced load vector can be smoothed with local algorithms. For technical reasons, the vast majority of previous work focuses on regular or almost regular graphs including ...

5
July 2015 ICALP 2015: Proceedings, Part II, of the 42nd International Colloquium on Automata, Languages, and Programming - Volume 9135
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

For understanding the structure of the resulting graphs and for analyzing the behavior of network algorithms, the next question is bounding the size of the diameter. The only known bound is $$\mathcal {O}\log n^{32/3-\beta 5-\beta }$$ Kiwi and Mitsche. ANALCO, pp. 26---39, 2015. We present two much simpler proofs for ...

6
April 2015 Theoretical Computer Science: Volume 576 Issue C, April 2015
Publisher: Elsevier Science Publishers Ltd.
Bibliometrics:
Citation Count: 1

The k-Clique�problem is a fundamental combinatorial problem that plays a prominent role in classical as well as in parameterized complexity theory. It is among the most well-known NP-complete and W1]-complete problems. Moreover, its average-case complexity analysis has created a long thread of research already since the 1970s. Here, we continue ...
Keywords: Computational complexity, Clique, Parameterized complexity, Average-case

7
March 2015 Discrete Applied Mathematics: Volume 184 Issue C, March 2015
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

Finding cliques in graphs is a classical problem which is in general NP-hard and parameterized intractable. In typical applications like social networks or biological networks, however, the considered graphs are scale-free, i.e., their degree sequence follows a power law. Their specific structure can be algorithmically exploited and makes it possible ...
Keywords: Power law graph, Inhomogeneous random graph, Clique, Scale-free network

8
March 2015 Evolutionary Computation: Volume 23 Issue 1, Spring 2015
Publisher: MIT Press
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 0,   Downloads (12 Months): 6,   Downloads (Overall): 27

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Many optimization problems arising in applications have to consider several objective functions at the same time. Evolutionary algorithms seem to be a very natural choice for dealing with multi-objective problems as the population of such an algorithm can be used to represent the trade-offs with respect to the given objective ...
Keywords: Approximations, hypervolume indicator, multi-objective optimization, theory

9 published by ACM
October 2014 ACM Transactions on Algorithms (TALG): Volume 11 Issue 2, November 2014
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 4,   Downloads (12 Months): 41,   Downloads (Overall): 218

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We propose and analyze a quasirandom analogue of the classical push model for disseminating information in networks (“randomized rumor spreading”). In the classical model, in each round, each informed vertex chooses a neighbor at random and informs it, if it was not informed before. It is known that this simple ...
Keywords: broadcasting, expander, rumor spreading, Distributed computing, quasirandomness, random graphs

10
October 2014 Journal of Computer and System Sciences: Volume 81 Issue 1, February, 2015
Publisher: Academic Press, Inc.
Bibliometrics:
Citation Count: 0

We present a new randomized diffusion-based algorithm for balancing indivisible tasks (tokens) on a network. Our aim is to minimize the discrepancy between the maximum and minimum load. The algorithm works as follows. Every vertex distributes its tokens as evenly as possible among its neighbors and itself. If this is ...
Keywords: Random walk, Distributed computing, Randomized algorithms, Diffusion, Load balancing

11 published by ACM
July 2014 GECCO '14: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation
Publisher: ACM
Bibliometrics:
Citation Count: 10
Downloads (6 Weeks): 1,   Downloads (12 Months): 23,   Downloads (Overall): 121

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The goal of bi-objective optimization is to find a small set of good compromise solutions. A common problem for bi-objective evolutionary algorithms is the following subset selection problem (SSP): Given n solutions P ⊂ R 2 in the objective space, select k solutions P* from P that optimize an indicator ...
Keywords: measurement, epsilon indicator, hypervolume indicator, archiving algorithms, performance

12
November 2013 Artificial Intelligence: Volume 204, November, 2013
Publisher: Elsevier Science Publishers Ltd.
Bibliometrics:
Citation Count: 6

Many state-of-the-art evolutionary vector optimization algorithms compute the contributing hypervolume for ranking candidate solutions. However, with an increasing number of objectives, calculating the volumes becomes intractable. Therefore, although hypervolume-based algorithms are often the method of choice for bi-criteria optimization, they are regarded as not suitable for many-objective optimization. Recently, Monte ...
Keywords: Evolutionary algorithm, Hypervolume indicator, Multi-objective optimization, Pareto-front approximation

13
July 2013 ICALP'13: Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part I
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 1

The standard algorithm for fast generation of Erdős-Rényi random graphs only works in the Real RAM model. The critical point is the generation of geometric random variates Geo( p ), for which there is no algorithm that is both exact and efficient in any bounded precision machine model. For a ...

14
July 2013 ICALP'13: Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part I
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 4

We initiate the study of job scheduling on related and unrelated machines so as to minimize the maximum flow time or the maximum weighted flow time (when each job has an associated weight). Previous work for these metrics considered only the setting of parallel machines, while previous work for scheduling ...

15 published by ACM
July 2013 GECCO '13: Proceedings of the 15th annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 1,   Downloads (12 Months): 7,   Downloads (Overall): 71

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The hypervolume indicator (HYP) is a popular measure for the quality of a set of n solutions in ℜR d . We discuss its asymptotic worst-case runtimes and several lower bounds depending on different complexity-theoretic assumptions. Assuming that P ≠ NP, there is no algorithm with runtime poly( n,d ). ...
Keywords: theory, performance measures, selection, multiobjective optimization

16
February 2013 Theoretical Computer Science: Volume 472, February, 2013
Publisher: Elsevier Science Publishers Ltd.
Bibliometrics:
Citation Count: 1

We examine the complexity of constraint satisfaction problems that consist of a set of AllDiff constraints. Such CSPs naturally model a wide range of real-world and combinatorial problems, like scheduling, frequency allocations, and graph coloring problems. As this problem is known to be NP-complete, we investigate under which further assumptions ...

17
February 2013 Artificial Intelligence: Volume 195, February, 2013
Publisher: Elsevier Science Publishers Ltd.
Bibliometrics:
Citation Count: 8

In order to allow a comparison of (otherwise incomparable) sets, many evolutionary multi-objective optimizers use indicator functions to guide the search and to evaluate the performance of search algorithms. The most widely used indicator is the hypervolume indicator. It measures the volume of the dominated portion of the objective space ...
Keywords: Evolutionary computation, Multi-objective optimization, Approximation, Hypervolume indicator, Selection, Theory

18
October 2012 Theoretical Computer Science: Volume 456, October, 2012
Publisher: Elsevier Science Publishers Ltd.
Bibliometrics:
Citation Count: 5

Multi-objective optimization deals with the task of computing a set of solutions that represents possible trade-offs with respect to a given set of objective functions. Set-based approaches such as evolutionary algorithms are very popular for solving multi-objective optimization problems. Convergence of set-based approaches for multi-objective optimization is essential for their ...
Keywords: Evolutionary algorithms, Performance measures, Set-based optimization, Hypervolume indicator, Convergence, Multi-objective optimization

19 published by ACM
July 2012 GECCO '12: Proceedings of the 14th annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 0,   Downloads (12 Months): 10,   Downloads (Overall): 80

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We study the convergence behavior of (μ+λ)-archiving algorithms. A (μ+λ)-archiving algorithm defines how to choose in each generation μ children from μ parents and λ offspring together. Archiving algorithms have to choose individuals online without knowing future offspring. Previous studies assumed the offspring generation to be best-case. We assume the ...
Keywords: multiobjective optimization, theory, performance measures, selection

20
September 2010 Evolutionary Computation: Volume 18 Issue 3, Fall 2010
Publisher: MIT Press
Bibliometrics:
Citation Count: 0

The hypervolume indicator serves as a sorting criterion in many recent multi-objective evolutionary algorithms MOEAs. Typical algorithms remove the solution with the smallest loss with respect to the dominated hypervolume from the population. We present a new algorithm which determines for a population of size n with d objectives, a ...



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