Title

Testing parallelization paradigms for MOEAs

Document Type

Conference Proceeding

Publisher

Association for Computing Machinery, Inc

Faculty

Computing, Health and Science

School

School of Computer and Information Science

RAS ID

5414

Comments

Originally published as: Gamhewa, S., Hingston, P.F. (2008). Testing parallelization paradigms for MOEAs. In the proceedings of the Genetic Algorithms and Evolutionary Computation Conference. Atlanta, USA: Genetic Algorithms and Evolutionary Computation Conference (pp. 755 - 756).

Abstract

In this paper, we report on our investigation of factors affecting the performance of various parallelization paradigms for multiobjective evolutionary algorithms. Different parallelization paradigms emphasize separate development of sub-populations versus communication and coordination between sub-populations to greater or lesser degrees. We hypothesized that the characteristics of a particular problem will favour some paradigms over others. We tested this hypothesis by creating variations on test problems with different characteristics, and testing the performance of different paradigms in a cluster environment.

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