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Reviewers have now returned comments on your paper. Your manuscript, in its current form, is unacceptable for publication   Both Reviewers, albeit that Reviewer #1 provided limited feedback, require you to provide more details, validation, and clarification.  I have also examined the manuscript and agree with their assessments.  I am willing to consider a revised submission from you if, at a minimum, you thoroughly address all the issues stated by both Reviewers.
If you decide to revise the work, please submit a list of changes or a rebuttal against each point which is being raised when you submit the revised manuscript.  Please also highlight any changes and/or additions made in the revised submission.
I would hope you can submit your revised paper to the Journal by 20/04/2015. If this is not possible please make the Journal Office aware.

Kind regards,
Reviewer comments and recommendations:
Reviewer #1: I would like to see more details about the computational approach and the elements that were used as well as about the expected level of deviation between simulations and experimental data.
Reviewer #2: The paper has presented an interesting work in optimization. Since the optimization of traditional structure has been extensively studied, this paper should present its innovation in the new reinforced structure or optimization method. Currently, no direct test data in the paper are available to confirm the validation of the FE model. Moreover, it is not clear to the reviewer that how the optimization algorithm (MOPSO) is implemented and how it is superior to other methods (like NSGA-II). Overall, further work is needed for journal publication:

1. In section 5.3, the algorithms should be compared to other up-to-date methods such as NSGA-II, not old version of NSGA. If possible, provide the comparison of MOPSO results and the NSGA-II results (either using software or Software of Deb.).
2. Please indicate whether the authors developed the optimization algorithm (MOPSO) or use some software to implement the optimization process. Meanwhile, how the sampling number of 20 (Table 1) is chosen?
3. For the expression of objective function, please write in standard mathematical way, say min (f1, f2), and min -SEAm is suggested. Also, please check the  Fig.13, and indicate how to determine the preferred solution (i.e. the knee point) from the Pareto fronts for two-objective optimization problem except for some specific decision-making criteria.
4. How many hours for the CAE runs vs. surrogate model runs using RSM. What is the machine configuration?
5. Please indicate the meaning of symbols (<sigma>, <epsilon> in Fig.11

6. In the formulation (6), check the symbol p (lower case), or P?
7. Check the reference of tables, should be consistent (Table or Tab.).
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