![](bg8.png)
Figure 3: The Graphical Representation of Statistical Anal-
ysis with Friedman’s test and Bonferroni-Dunn’s method.
is proved that the proposed D-HMP-CA is a scalable
method such that it offers competitive performance to
solve large scale global optimization problems com-
pared to the state-of-the-art methods.
Although D-HMP-CA offers a great performance
to solve large scale global optimization problems, it
can be further improved by incorporating more ad-
vanced decomposition strategies. Detecting variable
interactions in dimension decomposition approach is
considered as future direction for this research.
ACKNOWLEDGEMENTS
This work is made possible by the support from
the National Science Foundation under Grant DEB-
0816400 and NSERC Discovery under Grant No.
327482.
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