Populations Can Be Essential in Tracking Dynamic Optima-Reference-Cited by-同舟云学术

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Populations Can Be Essential in Tracking Dynamic Optima

Published:2016-08-26 Issue:2 Volume:78 Page:660-680
ISSN:0178-4617
Container-title:Algorithmica
language:en
Short-container-title:Algorithmica

Author:

Dang Duc-Cuong,Jansen Thomas,Lehre Per Kristian

Funder

Seventh Framework Programme

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,General Computer Science

Link

http://link.springer.com/content/pdf/10.1007/s00453-016-0187-y.pdf

Reference22 articles.

1. Branke, J., Wang, W.: Theoretical analysis of simple evolution strategies in quickly changing environments. In: Proceedings of the 5th Annual Conference on Genetic and Evolutionary Computation, GECCO’03, pp. 537–548. (2003)

2. Dang, D.-C., Jansen, T., Lehre, P.K.: Populations can be essential in dynamic optimisation. In: Proceedings of the 17th Annual Conference on Genetic and Evolutionary Computation Conference, GECCO’15, pp. 1407–1414. ACM (2015)

3. Dang, D.-C., Lehre, P.K.: Runtime analysis of non-elitist populations: from classical optimisation to partial information. Algorithmica 75(3), 428–461 (2016)

4. Droste, S.: Analysis of the (1+1) EA for a dynamically bitwise changing OneMax. In: Proceedings of the 2003 International Conference on Genetic and Evolutionary Computation, GECCO’03, pp. 909–921. Springer (2003)

5. Droste, S., Jansen, T., Wegener, I.: On the analysis of the (1+1) Evolutionary Algorithm. Theor. Comput. Sci. 276, 51–81 (2002)

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