Notice of RetractionSearching for robust optimal solutions by an evolutionary algorithm

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

When searching for robust optimal solutions in evolutionary optimization, a criterion for robustness estimation is needed. An expectation-based approach and a variance-based approach are highlighted in this paper. Experiments are conducted on a single-objective test function adopting three unequal values of dimension size, solved by an chaotic evolutionary algorithm. In both former low-dimensional cases, graphical results are given to make a visual comparison between the two robustness measures, which shows that their searching ability is complementary. Then a dominance mechanism similar to the definition of domination in multi-objective optimization is suggested, and integrated with chaotic evolutionary algorithm for selection of a survival between two individuals in single-objective evolutionary optimization. In the third high-dimensional case, solved by modified chaotic evolutionary algorithm with variance-based measure approach, good numerical results are reported.