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Article
Peer-Review Record

Dynamic Optimization of Construction Time-Cost for Deep and Large Foundation Pit Based on BIM Technology and Genetic Algorithm

Appl. Sci. 2023, 13(19), 10716; https://doi.org/10.3390/app131910716
by Yingxia Yu 1,*, Junjia Han 2, Haoyu Gu 1 and Yi Yang 3
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Appl. Sci. 2023, 13(19), 10716; https://doi.org/10.3390/app131910716
Submission received: 2 September 2023 / Revised: 18 September 2023 / Accepted: 22 September 2023 / Published: 26 September 2023
(This article belongs to the Section Civil Engineering)

Round 1

Reviewer 1 Report

1.     Abstract needs to be further improved. Some background of current study need to be provided. The overview of proposed methodology needs to be explained with better clarity.

2.     Problem statements that motivate current study need to be elaborated. What are the challenges that are being addressed in current study?

3.     Technical contributions of current study need to be highlighted.

4.     It is also crucial for authors to highlight the differences between the proposed work and those published works.

5.     The solution encoding process of GA needs to be illustrated. It is not clear what are the decision parameters to be optimized in this case. It is mentioned that there are 27 genes representing 27 works, but each gene has multiple attributes. So, what will be the dimensional size of each gene when considering all attributes of 27 genes? Please clarify this issue.

6.     More detailed explanations need to be provided for the mutation, crossover, and selection process. There could be many different variations of mutation, crossover and selection operators published and it is crucial for authors to provide the mathematical equations used.

7.     The workflow of the proposed method is not clearly demonstrated in Fig 2. Please provide a more comprehensive diagram to better illustrate the workflow. Furthermore, the dotted line has overlapped with some block modules such as "BIM module" and "Project parameter information". This should be avoided.

8.     What are the meanings of GZ, GL, WT and ZH? Please clarify.

9.     What are the upper and lower limits of decision variables to be optimized in this study? Authors did not mention about this in their manuscript.

10.  One of my concerns on this manuscript is that there are no performance comparison done at all. It is hard to justify whether the results obtained by GA are sufficiently good. There should be some baseline methods used for comparison purpose.

11.  Quality of Figure 3 is not satisfactory and needs further improvement.

No major issues with English

Author Response

Dear reviewers, we have made modifications based on the review comments and written a modification note. For more details, please refer to the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The presented manuscript seems to be interesting for readers of the Applied Sciences journal, it is written in a good manner and suits the requirements of the journal. It can be accepted for publication after minor corrections listed below.

- The "Abstract" section should contain the main achievements of research not general discussion. Re-organization of abstract is needed.

- State of the art to be improved further.

- What was the basis for choosing the parameters? Why are the experimental design methods not used in the selection of variables and their levels?

- All parameters used in formulas must be explained. It is recommended to attach all parameters and abbreviations used in a table at the end of the article.

- Abbreviation/ acronyms, should all be defined at their first occurrence in the manuscript,

- In the "Conclusion" section, the authors should present more quantitative data as the main results of the research study rather than just some qualitative data.

- Literature review is not sufficient and authors must review and cite more papers in the field of “predicting properties based on artificial intelligence“. Doing this, review and citing the following refs could be helpful:

Neural Network World  23, no. 4 (2013): 351-368., Neural Network World 23, no. 2 (2013): 117.,

Minor editing of English language required

Author Response

Dear reviewers, we have made modifications based on the review comments and written a modification note. For more details, please refer to the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear authors,

Please address the comments.

1. Few more numerical highlights is to be added in Abstract.

2. Keywords are like lengthy sentences, try to modify it.

3 How it is stated that BIM model is both qualitative and quantitative are reliable? It needs justification.

4. The construction time is arrived as 118 days as critical route, what about other routes and its duration?

5. What is the significance of dynamic optimization model in this study?

6. What is the difference between contact time and planned time?

7. Why huge difference between limit time and direct cost rate among GZ and GL? Try to clarify it.

8. Conclusion part needs some more details as an major outcome of the work.

9. Add few latest references in the study. 

It needs some minor changes.

Author Response

Dear reviewer, we have made modifications according to the review comments and written a modification note. Please see the attachment for details.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Authors have addressed all comments given. No further comments.

No major issues with the English Language quality

Reviewer 2 Report

As authors have performed an adequate revise, the manuscript might be accepted for publication in the Journal. 

Minor editing of English language required.

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