Review History


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Summary

  • The initial submission of this article was received on November 22nd, 2024 and was peer-reviewed by 2 reviewers and the Academic Editor.
  • The Academic Editor made their initial decision on February 3rd, 2025.
  • The first revision was submitted on May 7th, 2025 and was reviewed by 2 reviewers and the Academic Editor.
  • A further revision was submitted on June 14th, 2025 and was reviewed by 1 reviewer and the Academic Editor.
  • The article was Accepted by the Academic Editor on July 9th, 2025.

Version 0.3 (accepted)

· Jul 9, 2025 · Academic Editor

Accept

Reviewers are satisfied with the revisions, and I concur to recommend accepting this manuscript.

Reviewer 3 ·

Basic reporting

The author has fixed general language issues in their revised manuscript. The overall flow is clear and solid.

Experimental design

Overall design is robust. While it's still limited by its sole computational-based nature, the overall design is good.

Validity of the findings

The have provided ample evidence to support their conclusion. The limitations, generalizability, and scalability are also discussed in the manuscript.

Version 0.2

· May 28, 2025 · Academic Editor

Minor Revisions

There are some remaining minor concerns that need to be addressed.

Reviewer 2 ·

Basic reporting

All comments can be found in the last section.

Experimental design

All comments can be found in the last section.

Validity of the findings

All comments can be found in the last section.

Additional comments

Review Report for PeerJ Computer Science
(Comparing variable neighbourhood search algorithms for the direct aperture optimisation in radiotherapy)

Responses to reviewer comments and changes made to the paper based on these are generally at an appropriate level.

Reviewer 3 ·

Basic reporting

The revised manuscript shows clear improvement in language and corrected grammatical errors. The narrative is better written and easier to follow, compared to the previous version. The paper is well-structured and the figures are well-designed, clearly conveying the message intended to deliver.

Experimental design

1. Although the author has presented a strong study on prostate cancer, a discussion on the adaptability of the method should be included, especially those with more complex anatomical sites.
2. While runtime is not a major concern, this manuscript could be strengthened by a commentary on computation cost and runtime scalability, especially for rVNS, as this can be important for clinical translation and broader adoption.

Validity of the findings

1. Though this was brought up in prior review, the justification for focusing solely on prostate cancer remains limited. The study only included a small number of cases (5 from each dataset), which impairs the generalizability and reliability of the conclusion. Plans for future validation with larger and more diverse dataset should be included.
2. Given that the aperture number and does trade-off are critical to the algorithm's output, the author should discuss the sensitivity of the results to parameter settings.

Version 0.1 (original submission)

· Feb 3, 2025 · Academic Editor

Major Revisions

The reviewers have substantial concerns about this manuscript. The authors should provide point-to-point responses to address all the concerns and provide a revised manuscript with the revised parts being marked in different color.

Note that the comments for R1 are in their PDF document

[# PeerJ Staff Note: It is PeerJ policy that additional references suggested during the peer-review process should *only* be included if the authors are in agreement that they are relevant and useful #]

Reviewer 1 ·

Basic reporting

No comment.

Experimental design

Comments provided in the attached doc.

Validity of the findings

Comments provided in the attached doc.

Additional comments

No comments.

Annotated reviews are not available for download in order to protect the identity of reviewers who chose to remain anonymous.

Reviewer 2 ·

Basic reporting

All comments have been added in detail to the last section.

Experimental design

All comments have been added in detail to the last section.

Validity of the findings

All comments have been added in detail to the last section.

Additional comments

Review Report for PeerJ Computer Science
(Comparing variable neighbourhood search algorithms for the direct aperture optimisation in radiotherapy)

1. In the study, two different algorithms were proposed for direct aperture optimization in the field of radiotherapy.

2. In the introduction section, cancer, intensity modulated radiation therapy, the importance and details of the subject, the Direct Aperture Optimization problem and literature were mentioned. First of all, a detailed literature review consisting of columns such as "originality, positive aspects, negative aspects, method" should be added to this section. After this, the differences of the study from the literature, its contributions to the literature and originality points should be added to the end of this section after the literature table in a more detailed manner.

3. The Direct Aperture Optimization problem was clearly mentioned. In addition, the details regarding variable neighborhood search algorithms are sufficient and explanatory.

4. The use of the CERR dataset as a dataset in the study was specified. It should be explained in detail why this dataset was preferred compared to other datasets in the literature and whether different experiments were made.

5. The number of apertures used, the beam-on time and the objective function value metrics used in the study are sufficient for the analysis of the study. In addition, when these metric results are examined, it is observed that they are at a certain level and appropriate.

As a result, it is very important to pay attention to the above sections for this study related to direct aperture optimization in order to increase the contribution of the study to the literature.

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