Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation 2011
DOI: 10.1145/2001576.2001790
|View full text |Cite
|
Sign up to set email alerts
|

On the effectiveness of crossover for migration in parallel evolutionary algorithms

Abstract: Island models are popular ways of parallelizing evolutionary algorithms as they can decrease the parallel running time at low communication costs and lead to an increased population diversity. This in particular provides a good setting for crossover as this operator relies on a good diversity between parents. We consider the effect of recombining migrants with individuals on the target island. We rigorously prove, for a test function in pseudo-Boolean optimization, exponential performance gaps between island m… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

1
40
0

Year Published

2012
2012
2024
2024

Publication Types

Select...
6
2
2

Relationship

3
7

Authors

Journals

citations
Cited by 39 publications
(41 citation statements)
references
References 17 publications
1
40
0
Order By: Relevance
“…However, these techniques cannot be directly applied to the analyses of more realistic GAs incorporating a crossover operator. Several results were indeed available proving that crossover is useful (Jansen and Wegener, 2005;Watson and Jansen, 2007;Oliveto et al, 2008;Doerr et al, 2010;Kötzing et al, 2011;Neumann et al, 2011;Sudholt, 2012;Doerr et al, 2013), but they rely heavily on elitist selection operators. Moreover, mostly only upper bounds on the running time of crossover-based algorithms were available.…”
Section: Introductionmentioning
confidence: 99%
“…However, these techniques cannot be directly applied to the analyses of more realistic GAs incorporating a crossover operator. Several results were indeed available proving that crossover is useful (Jansen and Wegener, 2005;Watson and Jansen, 2007;Oliveto et al, 2008;Doerr et al, 2010;Kötzing et al, 2011;Neumann et al, 2011;Sudholt, 2012;Doerr et al, 2013), but they rely heavily on elitist selection operators. Moreover, mostly only upper bounds on the running time of crossover-based algorithms were available.…”
Section: Introductionmentioning
confidence: 99%
“…Lässig and Sudholt [8] presented a method for analysing speedups in island models, and applications to combinatorial problems [10]. Neumann, Oliveto, Rudolph, and Sudholt [15] considered the benefit of crossover during migration for artificial problems and instances of the Vertex Cover problem. Mambrini, Sudholt, and Yao [14] studied the running time and communication effort of homogeneous and heterogeneous island models for finding good solutions for the NP-hard Set Cover problem.…”
Section: Related Workmentioning
confidence: 99%
“…Moreover, general results on the speedup achievable through different topologies are available [16]. It is also known that island models can support the effect of crossover [21] and yield exponential speedups on specific examples. Still, to the best of our knowledge, runtime analyses of parallel EAs on dynamic optimization problems have not been available so far.…”
Section: Introductionmentioning
confidence: 99%