PONE-D-24-05998Shared Manufacturing Service Composition Optimization Based on Bi-Level ProgrammingPLOS ONE

Dear Dr. Liu,

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Kind regards,

Van Thanh Tien Nguyen, Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

Reviewer #3: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Author(s),

Your manuscript titled “Shared Manufacturing Service Composition Optimization Based on Bi-Level Programming” is now assessed. The topic is really interesting and applicable, but in the current form it needs further processing and obviating shortcomings. I list concerns and issues for your perusal. It can be re-submitted provided the issues are addressed.

1- The English should be improved. The whole proofreading is appreciated.

2- The abstract should be re-written to enhance its quality. Adding the novelty and also numerical achievements in abstract is appreciated. Please put percentage improvement.

3- In abstract, you should mention the objective function is a cost-function which needs to be minimized.

4- What does CRITIC stand for? Please uses extracted from before the first usage of abbreviation. Please perform in all parts.

5- I recommend the title needs changing because it would be more specified when you indicate your algorithm. It seems the current title does not convey the main goal especially NSGA-II.

6- The keywords are insufficient. Please add ample and the most relevant keywords.

7- The used references are imperfect. Please rectify or update all references in terms of data, pages, doi, etc. In addition, more newly published and the most relevant papers should be added in some parts to increase the quality of paper and attracts more researchers’ attention on your manuscript. If possible for you, please omit old-fashioned or un-reputed papers and index-less journals from citation and reference list to enhance the manuscript authentication.

8- One of the most important thing that you used is NSGA-II algorithm. Please explain about it in literature review. Please cite this reference “K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," in IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182-197, April 2002, doi: 10.1109/4235.996017.”

9- In introduction section, please enlist contributions in bullet form, before paper structure is introduced.

10- The re-structure is necessary for your manuscript. It lacks literature review and related work. Please add related work.

11- Related work should be extended. I recommend mention some papers below to improve the quality of current paper. Firstly, introduce NSGA-II, non-dominated solutions, and Pareto set concepts. Please use reference ““K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," in IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182-197, April 2002, doi: 10.1109/4235.996017.”” with suitable citation.

The bi-level programming needs to be introduced with suitable reference. Please add couple of relevant papers in related work.

Service composition technology is used in several industries to reduce overall cost; also, this technology is engaged to improve reliability, security, etc. In IT industry, a decision model paper titled “An iterative mathematical decision model for cloud migration: A cost and security risk approach” was extended to indicate how service composite is beneficial for individuals and businesses.

Bi-objective web service composition algorithm entitled “Bi-objective web service composition problem in multi-cloud environment: a bi-objective time-varying particle swarm optimisation algorithm” was proposed to reduce overall cost and increase security in multi-cloud environment.

Recently published reliability –aware service composition method in paper titled “Reliability-aware web service composition with cost minimization perspective: a multi-objective particle swarm optimization model in multi-cloud scenarios” was proposed to increase system reliability.

A genetic algorithm was extended to solve web service composition problem in “Optimization of Automatic web services composition using genetic algorithm” for distributed systems.

12- Is your algorithm heuristic or meta-heuristic? Why?

13- Since you used GA, what is problem encoding? Termination criteria? Please put condensed sentences about my questions.

14- Is your algorithm scalable?

15- What is implementation environment? Please put condense explanation about implementation/simulation environment. More experiments are recommended to reach concrete results and conclusion.

16- The conclusion should be changed to “Conclusion and future direction”. Please put a condense sentence about limitation of your work. And what is the future direction?

In the current form, I cannot accept it publication, but it can be re-evaluated provided the issues are carefully addressed. Therefore, I recommend Major revision.

Reviewer #2: The authors have addressed my concerns and presented convincing answers to them except my 6th and 7th concerns. I have repeated these concerns below. Please note that based on my 6th concern, you MUST compare your improved algorithm with the conventional one upon implementing both algorithms on a set of popular standard test functions. Furthermore, I requested the authors to revise the English of the manuscript in my 7th comment, however, after reading the revised version of the manuscript; I found out that the English of the paper HAS NOT BEEN IMPROVED enough. The manuscript would be accepted for publication if and only if these two concerns are fully addressed and removed.

6. It is recommended to first test the competence of your improved NSGA-II algorithm on a set of standard benchmark test functions and to compare the results with those of the conventional NSGA-II algorithm prior to go over solving the practical problem introduced in the manuscript.

7. The English of the manuscript can be and should be improved. There are considerable grammatical errors in the text of the manuscript that should be removed in the revised version.

Reviewer #3: As a reviewer, I commend the authors for addressing the critical issue of service composition optimization in shared manufacturing environments. The proposed bi-level programming approach appears to be a promising method for enhancing service quality by considering reliability, trustworthiness, and task fit. Here are my comments and suggestions:

1. Clarity of Abstract:

The abstract is generally well-written, but it could be more concise. It would benefit from a tighter focus on the main contributions of the paper, such as the novel application of the CRITIC method and the improved NSGA-II algorithm.

2. Methodology:

The authors should provide a more detailed explanation of how the CRITIC method is utilized to determine the weights of the indicators. For example, through the analysis of contrast and ambivalence, how to connect to the weighted formula.

3. Case Study and Experimental Results:

It is essential to validate the proposed model with a comprehensive case study or multiple case studies. The experimental results should include a sensitivity analysis to demonstrate how the model responds to variations in input parameters.

4. Future Work:

While the discussion on future work is informative, it would be beneficial to include some direction on how the proposed model can be extended to accommodate dynamic changes in the shared manufacturing environment, such as fluctuating demand or the entry of new service providers.

In summary, this paper presents a valuable addition to the field of shared manufacturing service composition. With further refinement and clarification of the methods and results, it has the potential to make a significant impact on both researchers and practitioners in the field.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Bi-Level Optimization of Shared Manufacturing Service Composition Based on Improved NSGA-II

PONE-D-24-05998R1

Dear Dr. Liu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Van Thanh Tien Nguyen, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: (No Response)

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Author(s),

Thanks for your attempt to obviate shortcomings,

The issues have been addressed. The manuscript is eligible for publication.

Reviewer #2: I appreciate the efforts of the authors to improve the technical aspects of the manuscript. The manuscript is accepted for publication as is.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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