Frank Neumann
Frank Neumann
Optimisation and Logistics, School of Computer
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Cited by
Cited by
Bioinspired computation in combinatorial optimization: algorithms and their computational complexity
F Neumann, C Witt
Springer, 2010
Randomized local search, evolutionary algorithms, and the minimum spanning tree problem
F Neumann, I Wegener
Theoretical Computer Science 378 (1), 32-40, 2007
On the effects of adding objectives to plateau functions
D Brockhoff, T Friedrich, N Hebbinghaus, C Klein, F Neumann, E Zitzler
IEEE Transactions on Evolutionary Computation 13 (3), 591-603, 2009
Minimum spanning trees made easier via multi-objective optimization
F Neumann, I Wegener
Natural Computing 5 (3), 305-319, 2006
Runtime analysis of a simple ant colony optimization algorithm
F Neumann, C Witt
Algorithmica 54 (2), 243, 2009
Approximating covering problems by randomized search heuristics using multi-objective models
T Friedrich, J He, N Hebbinghaus, F Neumann, C Witt
Evolutionary Computation 18 (4), 617-633, 2010
Optimal fixed and adaptive mutation rates for the LeadingOnes problem
S Böttcher, B Doerr, F Neumann
International Conference on Parallel Problem Solving from Nature, 1-10, 2010
Ant colony optimization and the minimum spanning tree problem
F Neumann, C Witt
Theoretical Computer Science 411 (25), 2406-2413, 2010
Expected runtimes of a simple evolutionary algorithm for the multi-objective minimum spanning tree problem
F Neumann
European Journal of Operational Research 181 (3), 1620-1629, 2007
A comprehensive benchmark set and heuristics for the traveling thief problem
S Polyakovskiy, MR Bonyadi, M Wagner, Z Michalewicz, F Neumann
Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014
Analyzing hypervolume indicator based algorithms
D Brockhoff, T Friedrich, F Neumann
International Conference on Parallel Problem Solving from Nature, 651-660, 2008
A fast and effective local search algorithm for optimizing the placement of wind turbines
M Wagner, J Day, F Neumann
Renewable energy 51, 64-70, 2013
Approximation-guided evolutionary multi-objective optimization
K Bringmann, T Friedrich, F Neumann, M Wagner
Twenty-Second International Joint Conference on Artificial Intelligence, 2011
Expected runtimes of evolutionary algorithms for the Eulerian cycle problem
F Neumann
Computers & Operations Research 35 (9), 2750-2759, 2008
Expected runtimes of evolutionary algorithms for the Eulerian cycle problem
F Neumann
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No …, 2004
Analysis of different MMAS ACO algorithms on unimodal functions and plateaus
F Neumann, D Sudholt, C Witt
Swarm Intelligence 3 (1), 35-68, 2009
Precipitation variability in the winter rainfall zone of South Africa during the last 1400 yr linked to the austral westerlies.
JC Stager, PA Mayewski, J White, BM Chase, FH Neumann, ...
Climate of the Past 8 (4), 2012
Automated algorithm selection: Survey and perspectives
P Kerschke, HH Hoos, F Neumann, H Trautmann
Evolutionary computation 27 (1), 3-45, 2019
Theoretical analysis of fitness-proportional selection: landscapes and efficiency
F Neumann, PS Oliveto, C Witt
Proceedings of the 11th Annual conference on Genetic and evolutionary …, 2009
Multiplicative Approximations, Optimal Hypervolume Distributions, and the Choice of the Reference Point
T Friedrich, F Neumann, C Thyssen
Evolutionary computation 23 (1), 131-159, 2015
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