Fitness Landscapes Based on Sorting and Shortest Paths Problems
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Evolutionary Algorithms and the Maximum Matching Problem
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Worst-case and average-case approximations by simple randomized search heuristics
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
IEEE Transactions on Evolutionary Computation
Biased mutation operators for subgraph-selection problems
IEEE Transactions on Evolutionary Computation
On the runtime analysis of the 1-ANT ACO algorithm
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Do additional objectives make a problem harder?
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Adjacency list matchings: an ideal genotype for cycle covers
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Rigorous analyses of simple diversity mechanisms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Speeding up evolutionary algorithms through asymmetric mutation operators
Evolutionary Computation
Analyses of simple hybrid algorithms for the vertex cover problem*
Evolutionary Computation
Drift analysis with tail bounds
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Revisiting the restricted growth function genetic algorithm for grouping problems
Evolutionary Computation
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We investigate the effect of restricting the mutation operator in evolutionary algorithms with respect to the runtime behavior. For the Eulerian cycle problem; we present runtime bounds on evolutionary algorithms with a restricted operator that are much smaller than the best upper bounds for the general case. It turns out that a plateau that both algorithms have to cope with is left faster by the new algorithm. In addition, we present a lower bound for the unrestricted algorithm which shows that the restricted operator speeds up computation by at least a linear factor.