
Open access
Date
2019-02-15Type
- Journal Article
Abstract
We study sorting of permutations by random swaps if each comparison
gives the wrong result with some fixed probability p < 1/2. We use this process as
prototype for the behaviour of randomized, comparison-based optimization heuristics
in the presence of noisy comparisons. As quality measure, we compute the expected
fitness of the stationary distribution. To measure the runtime, we compute the minimal
number of steps after which the average fitness approximates the expected fitness of
the stationary distribution. We study the process where in each round a random pair
of elements at distance at most r are compared. We give theoretical results for the
extreme cases r = 1 and r = n, and experimental results for the intermediate cases.
We find a trade-off between faster convergence (for large r) and better quality of the
solution after convergence (for small r). Show more
Permanent link
https://doi.org/10.3929/ethz-b-000254382Publication status
publishedExternal links
Journal / series
AlgorithmicaVolume
Pages / Article No.
Publisher
SpringerSubject
Sorting; Random swaps; Evolutionary algorithms; Comparison-based; Noise; Optimization heuristicsOrganisational unit
03340 - Widmayer, Peter / Widmayer, Peter03672 - Steger, Angelika / Steger, Angelika
Funding
165524 - Energy-Tunable Combinatorial Algorithms (SNF)
Notes
Published in the Special Issue on "Theory of Genetic and Evolutionary Computation".
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.More
Show all metadata