Skip to main content

Research Repository

Advanced Search

Comparative analysis of two asynchronous parallelization variants for a multi-objective coevolutionary solver.

Zavoianu, Alexandru-Ciprian; Saminger-Platz, Susanne; Amrhein, Wolfgang

Authors

Susanne Saminger-Platz

Wolfgang Amrhein



Abstract

We describe and compare two steady state asynchronous parallelization variants for DECMO2++, a recently proposed multi-objective coevolutionary solver that generally displays a robust run-time convergence behavior. The two asynchronous variants were designed as trade-offs that maintain only two of the three important synchronized interactions / constraints that underpin the (generation-based) DECMO2++ coevolutionary model. A thorough performance evaluation on a test set that aggregates 31 standard benchmark problems shows that while both parallelization options are able to generally preserve the competitive convergence behavior of the baseline coevolutionary solver, the better parallelization choice is to prioritize accurate run-time search adaptation decisions over the ability to perform equidistant fitness sharing.

Citation

ZAVOIANU, A.-C., SAMINGER-PLATZ, S. and AMRHEIN, W. 2019. Comparative analysis of two asynchronous parallelization variants for a multi-objective coevolutionary solver. In Proceedings of the 2019 Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation (IEEE CEC 2019), 10-13 June 2019, Wellington, New Zealand. Piscataway: IEEE [online], article number 8790133, pages 3078-3085. Available from: https://doi.org/10.1109/CEC.2019.8790133

Conference Name 2019 Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation (IEEE CEC 2019)
Conference Location Wellington, New Zealand
Start Date Jun 10, 2019
End Date Jun 13, 2019
Acceptance Date Apr 5, 2019
Online Publication Date Aug 8, 2019
Publication Date Aug 8, 2019
Deposit Date Jul 9, 2019
Publicly Available Date Jul 9, 2019
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Pages 3078-3085
DOI https://doi.org/10.1109/CEC.2019.8790133
Keywords Multi-objective optimization; Asynchronous coevolution; Master-slave parallelization; Performance analysis
Public URL https://rgu-repository.worktribe.com/output/314979

Files





You might also like



Downloadable Citations