Fusion Swarm-Intelligence-Based Decision Optimization for Energy-Efficient Train-Stopping Schemes

Round 1

Reviewer 1 Report

Comments for author File: Comments.pdf

Author Response

Thank you for your valuable comments, so that we can better improve the paper, the details of the response are attached.

Author Response File: Author Response.docx

Reviewer 2 Report

The article “Fusion swarm intelligence-based decision optimization for energy-efficient train-stopping schemes” deal with effective decision-making for train operation and promote the intelligent operation of the train system.

 

The authors present several interesting approaches.

 

In the article, the state of the art in the literature is presented comprehensively and correctly in terms of the literature considered, its brief summary, and its relevance to the core findings of the author's own research.

 

The problem class is beyond the literature in the scheduling theory; especially to a higher applicability. Most important, they extend the actual research.

 

The numerical ones are well prepared. The pictures support the explanations of the text very well.

 

Finally, the results have been very well and critically analyzed.

 

Last but not least, in my opinion, the article meets the standard of the journal Applied Sciences.

 

Thus, I recommend to accept this paper.

Author Response

Thank you for your recognition of our work.

Author Response File: Author Response.docx

Reviewer 3 Report

Please see the attached file...

Comments for author File: Comments.pdf

Author Response

Thank you for your valuable comments, so that we can better improve the paper, the details of the response are attached.

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

All of the necessary additions and modifications are properly performed. All of the concerns, questions, and suggestions are addressed. This reviewer thinks that, the paper can now be accpted for publication.