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Article
Peer-Review Record

Design a Robust Logistics Network with an Artificial Physarum Swarm Algorithm

Sustainability 2022, 14(22), 14930; https://doi.org/10.3390/su142214930
by Zhengying Cai *, Yuanyuan Yang, Xiangling Zhang and Yan Zhou
Reviewer 1:
Reviewer 2:
Reviewer 4:
Sustainability 2022, 14(22), 14930; https://doi.org/10.3390/su142214930
Submission received: 25 September 2022 / Revised: 8 November 2022 / Accepted: 9 November 2022 / Published: 11 November 2022
(This article belongs to the Section Sustainable Transportation)

Round 1

Reviewer 1 Report

The research questions need to be addressed in the introduction section

Some of the citations and the equations need to be formatted according to the Journal format: 153-156

English language is good but some errors need to be corrected : 611, 637,

Research limitation should be stated in the conclusion section

Further elaborations in future research directions in the conclusion section

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Thanks for the opportunity to review the manuscript "Robust Optimization for Logistics Network Based on An Artificial Physarum Swarm Algorithm’’ by Zhengying et al.
Authors have used An Artificial Physarum Swarm Algorithm which is interesting.

Possibly, it could be useful to the wider research community. I have gone through the complete manuscript and found it an interesting study.

1.      It is not reflected any novelty. Author must serious about the novelty in the manuscript

2.      The Title, Abstract, and Conclusion should be more informative and concise.

3.      There are several errors, grammar, construction, etc. of the manuscript.

4.      Don’t reflect the entire finding of the research. Please update significantly.

5.      The conclusion section needs to improve and should be concise and informative

6.      The results section does not have sufficient details and lack novelty.

7.      L833-836 Not clear.

8.      Redraw Figure 1. Artificial Physarum swarm system for better resolution.

Throughout the manuscript there is a lot of redundancy, please take care.

With this, I recommend the paper for minor revision.

Best Wishes,

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

This submission presents a swarm intelligence-based scheduling optimization framework for improving logistic network robustness. To evaluate the performance of the proposed approach, the authors conducted an experiment utilizing data on Mexican highways.

After reading the paper, I find it difficult to recommend it for publication in Sustainability in its current form due to the lack of novelty and contribution. Nevertheless, please find below my remarks for this submission.

Comments:

·             I strongly recommend the authors to proofread the paper once more, since it contains several poor word-choices and grammatical errors. Some indicative examples:

-            On page 2, the sentence “Especially, in the past ten years, a strange…problems” is incoherent and problematic.

-            On page 3, please lowercase “Due” in “In addition, Due to its particularity”, since it is not at the beginning of the sentence.

-            On page 21, please revise “…extended our minds about the learning intelligence of single-cell living things” in order to be more comprehensible and to-the-point.

·             It is advisable to include author names prior to their respective reference number. For example:

-            On page 1, please replace “[3] designed a resilient…” with “Aymen et al. [3] designed a resilient…”.

-            On page 3, please replace “In the same year, Adamatzky et al. also…” with “In the same year, Adamatzky et al. [42] also…”

·             In Introduction, the paragraph “Additionally, the robust optimization and scheduling…for logistics network optimization” does not support the reason why the authors utilized a swarm intelligence algorithm for tackling routing problem. Did the authors implement this method due to its hotness in the relevant literature? Furthermore, given the high number of applications of swarm intelligence presented in the pertinent literature, the paper’s novelty is somewhat questionable.

·             Although the paper includes a number of papers related to the routing problem, the literature review greatly fails to illustrate the research gaps found in the pertinent literature, and clearly present the novelty and the motivation of the present work compared to relevant publications.

·             In the 4th section, the authors describe their proposed methodology. Although, it is not easy to comprehend the functionality methodology, due to the high number of equations and paragraphs. To this end, it is advisable to include a flowchart describing the steps, or components involved in the proposed methodology. Furthermore, the 4.5 subsection is not consistent with the section’s subject. Therefore, it should be removed, or placed in a different section.

·             In the 5th section, the authors stated that their experimental analysis was heavily based on the experimental scenario presented in Adamatzky et al. [15]. Given this statement, it seems that the authors attempted to re-verify the effectiveness of the physarum swarm approach in the aforementioned case-study, instead of implementing the approach in a new one. Thus, I believe that the experimental analysis is not sufficient to support the performance of the proposed approach. In this respect, the authors should revise their experimental analysis by focusing on a different experimental scenario. Furthermore, the performance of the presented algorithm was compared to that of other algorithms, such as ant colony algorithm. However, it is not clear how these algorithms are implemented in the context of the addressed problem. The authors should elaborate on that.

Given the results obtained by the conducted experiments, it is not clear how the presented approach could be considered as a cost-effective solution. Therefore, it would be useful to illustrate the applicability of the presented approach in real-world environments.

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

The article presents the original results of the research carried out by the authors. It brings a new insight into a possible solution to the problem of optimization of logistics networks, through the Physarum Sarm Algorithm. The structure of the article, and the methodological definition, including the analytical part, create a logical whole, bringing new knowledge that is subsequently discussed in the final part. The theoretical overview is elaborated on a specific case study, the transport network in Mexico. The article is written in a readable and comprehensible form, the formal and citation requirements are met.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

The authors addressed and responded adequately to my remarks and suggestions and the overall quality of the paper has been significantly improved

Author Response

Thank you for your valuable comments on this manuscript, which provides a very valuable reference for improving the quality of this manuscript. During this period, we carefully checked and proofread the full text again, polished the English, corrected many errors, and further improved the quality of the manuscript.

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