A Modeling Method for Emergency Rescue Center Siting Based on the Variable Butterfly Optimization Algorithm
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsDear author,
Thank you very much for the opportunity to read your research and provide a review.
The article is interesting, high-quality and scientific.
However, I recommend the following changes and have the following comments and suggestions:
- I suggest that when placing emergency centers, you also elaborate on the influences that may affect their location, especially the type of emergency event. You should also divide these events and characterize the influences on location according to existing research, which you will add to the publication sources.
- In Chapter 2, it is necessary to consider the location of these centers, such as their strategic location, also in relation to natural or human-made emergencies. In the case of a flood, the location is different from that of an earthquake or a terrorist attack. I would recommend adding something here.
- Figures 1-10 need to be reworked because the x-axis and y-axis are illegible, as are the legends in the figures.
- I recommend reworking the tables or placing them so that they do not exceed the page, as it is then difficult for the reader to understand the issue.
- In Chapter 4, you have tables where I would recommend justifying individual input variables such as vehicle speed and vehicle weight to make it more understandable for an uninterested reader.
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I would suggest adding a discussion to the article, where you would describe and characterize the uniqueness of your research and also its application in practice in solving an emergency.
Then add these comments to the conclusion.Thank you very much.
The article is scientific and professional, it has potential.
Author Response
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Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis work proposes a method for choosing the places of emergency centers in two steps, based on the Butterfly Optimization algorithm. In my opinion, the authors should treat:
- Abstract. Clearly state that the better performance was shown on the chosen experimental data.
- Introduction. "most optimal" is not correct, as "optimal" means the best.
- Section 2. The mathematical models do not explain the variables Xj, Yij, and Zij', and have no constraints. It is difficult to solve a problem with no constraints.
- Section 3. It is unclear in the standard BOA, which equation is applied: 7 or 8. Step 3 says that one of them, but gives no condition for choosing. The same for eq. 9. In eq. 10, k is not described. In eq. 11, j is not described. Figures 1 to 10 are not described - what data derived each of them? Why do the authors mention "predicted results"? What algorithms were used for comparisons? Please give a short description of each algorithm, and describe how the parameter values were chosen. Why only 100 iterations were considered? Table 2 - In the second part, the columns' names should change (not Kowalik, again, I think). The Salp Swarm Algorithm is mistakenly put in text.
- Section 4. Tables 4, 6 - 8 present only site 4? It is unclear how many instances were considered. I think that testing the proposed algorithm on one case does not allow to assess that it performs exceptionally well. Many other data tests are required. I suggest making the datasets open.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThis paper discusses the application of an improved variant butterfly optimization algorithm (VBOA) in the site selection of emergency material distribution centers. The topic is of great practical significance, because traditional site selection models often ignore the dynamic changes in material demand and fail to optimize in combination with real-time conditions. The VBOA algorithm proposed by the author has improved efficiency and fairness, which is a good innovation.
However, after reading it, I feel that there are several areas that can be further improved:
1. Abstract and conclusion
The abstract is a bit vague, as if it is written in a hurry. It is recommended to add the following explanations: (1) Why do we need to study this problem? (2) What exactly has VBOA improved? (3) How much better is the actual effect than the traditional method? The conclusion also ends too abruptly. It would be better to talk about: In what practical scenarios can this method be used? What are its limitations? How can it be optimized in the future?
2. References
The number of references is relatively small, especially related research in the past three years. It is recommended to add the following: (1) Application cases of other intelligent algorithms in emergency logistics; (2) The latest progress in the field of multi-objective optimization; (3) Empirical research comparing different algorithms.
3. Model construction
The formulas are very complete, but key details are missing: (1) Real-world resource constraints (such as budget and vehicle capacity) are not taken into account; (2) The applicability of the model in real scenarios has not been verified; (3) It is recommended to explain all variables clearly before piling up formulas, otherwise it is easy to be confused.
4. Experimental part
The experimental design is relatively complete, but there are several problems: (1) Why are these algorithms selected for comparison? What are their advantages and disadvantages? (2) The optimal results in the table should be bold and marked in red. It is very difficult to find them yourself now; (3) It is recommended to analyze the data immediately after each table is placed. Now the table and text are completely separated, and you will forget the previous content while reading; (4) If a significance test can be performed, the conclusion will be more convincing.
5. Formatting issues
• Tables 3 and 5 have wrong rows when displayed across pages
• The site numbers in Tables 4, 6, and 7 are inconsistent
• It is recommended to check the layout of all tables, especially the paging
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors failed to treat the items 3 and 5.
3. The variables are somehow explained, but they are not constraints of the mathematical model.
One old and usually described mathematical model is, for example, the Dantzig–Fulkerson–Johnson formulation for the Traveling Salesman Problem.
5. There is still one instance treated, and the results are compared against other algorithms. I suggest to test many instances, and to perform a statistical analysis, too.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors have thoroughly addressed nearly all of the comments raised in the previous review, resulting in a substantial improvement in both the clarity of the problem and the reinforcement of the prior work. I have no additional comments or suggestions for the authors at this stage.
Author Response
Comments 1: [The authors have thoroughly addressed nearly all of the comments raised in the previous review, resulting in a substantial improvement in both the clarity of the problem and the reinforcement of the prior work. I have no additional comments or suggestions for the authors at this stage.]
Response 1: [Thank you for your kind advice. We Agree with this comment. Your suggestions are of great help in our revision period and we have realized our limitations on our writing period. With your patience and agreement to our paper, the revised version have been better improved. Thank you for your valuable advice.]
Round 3
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors treated completely the raised issues.