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Article
Peer-Review Record

A Robust Optimization Model for Multi-Period Railway Network Design Problem Considering Economic Aspects and Environmental Impact†

Sustainability 2023, 15(6), 5022; https://doi.org/10.3390/su15065022
by Morteza Noruzi 1, Ali Naderan 1,*, Jabbar Ali Zakeri 2 and Kamran Rahimov 3
Reviewer 1:
Reviewer 2:
Reviewer 3:
Reviewer 4: Anonymous
Sustainability 2023, 15(6), 5022; https://doi.org/10.3390/su15065022
Submission received: 9 February 2023 / Revised: 8 March 2023 / Accepted: 9 March 2023 / Published: 12 March 2023

Round 1

Reviewer 1 Report

1. What is the innovation of the model proposed in this paper? Please highlight them in the paper.

2. The structure of the article chapters is not clear. The structure of the article chapters is not clear.

3. In the paper, the solution process using the NSGA-II method is extensively verified and compared. However, the extensive validation of the solution process does not prove the superiority of the proposed model. Please add comparisons of other models to demonstrate the superiority of the model.

4. The figure in the article contains errors and is crude. Please make corrections.

Author Response

we would like to thank the reviewer. The manuscript has been edited and proofread to address the reviewer's comments.

Author Response File: Author Response.pdf

Reviewer 2 Report

In this study, the authors are utilizing an optimization framework to deal with a railway network design problem under uncertainty. It is interesting and practical. However, I think the authors may take advantages of the following comments in order to improve the quality.

1) Introduction: this section should improve and give more idea about the problem, background and your contributions.

2) Literature review: this section must include more state-of-the-arts. I suggest the authors read the studies performed by scholars such as Ghasemi et al., Goodarzian et al., Tirkolaee et al., and their groups in this regard.

3) Model: Nice model is proposed. Please give more information on the superiority.

4) Solution algorithms: Give more details on the solution representation and Pareto fronts generation.

5) Discussion: Managerial insights are missing.

6) Conclusion: You may extend the future research directions by adding more ideas.

Author Response

We would like to thank the reviewer. The manuscript has been edited and proofread to address the reviewer's comments. 

Author Response File: Author Response.pdf

Reviewer 3 Report

I like the topic and think that it can be accepted after considering the major issues given in the following.

a. Novelties of your work should be explicitly explained in Abstract. 

b. Research questions and challenges are not discussed in the introduction section. 

c. Literature review can be enriched. I think more studies can be found to be reviewed and compared with your work.

d. Are the assumptions of the model based on the real-world situations?

e. Why did you apply robust optimization, for example, why did not you consider stochastic models?

f. How can you extend the model? please explain it.

g. Managerial insights are not provided at the end of results section.

h. Please improve English using a native speaker.

Author Response

We would like to thank the reviewer. The manuscript has been edited and proofread to address the reviewer's comments. 

Author Response File: Author Response.pdf

Reviewer 4 Report

This topic is interesting and seems applicable. The authors could provide a well-written manuscript. However, there are some issues to be addressed at this stage based on the following comments:

1- Please polish the English of the text. Please review the text again, there are some weird words in the text such as maintaining maintenance costs.

2- The backgrounds, problem significance, and challenges should be clearly discussed in the introduction section.

3- Update the literature review by including more recent studies from 2020 onwards.

4- Why did you choose eps-constraint and NSGA-II as solution algorithms?

5- Nice experiments are done, but the practical implications and theoretical insights are missing.

Author Response

We would like to thank the reviewer. The manuscript has been edited and proofread to address the reviewer's comments. 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The authors have made exhaustive revisions based on the review comments. 

Author Response

Thank you very much 

Reviewer 2 Report

No comment

Author Response

Thank you very mauch. The manuscript was edited and proofread to address reviewer,s comments

Reviewer 3 Report

The authors addressed the comments well. However, it would have helped the reviewer if they could have highlighted the new parts. I think there are still some issues to be addressed:

1- In [10]??? give the full information.

2- Highlight the main numerical achievements in the abstract.

Author Response

Thank you very much. The manuscript was edited and proofread to address reviewer's comments.   Best Regards  
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