An Iterative Backbone Algorithm for Service Network Design Problems

Round 1

Reviewer 1 Report

The subject is interesting and is aligned with the readership and the themes of this journal. However, the paper does not include enough evidence to support the claim. The following bullet points include some suggestions to improve the manuscript to be publishable.

·         Contributions of the paper are not mentioned in the Introduction section.

·         References must be updated and it seems that authors need to refer to latest work to justify the current approach

·         Figures have not cited, in text. Some of the figures in the manuscript are confusing because it is not clear what the meaning of the curve is.

·         The technical quality of this paper is quite low. Although theoretical concepts and related literature are properly introduced, some of the references are outdated and should be omitted. Moreover, the number of recent literature is low

·         Consider the following studies in the reference section:

1.         A New Initialization Approach in Particle Swarm Optimization for Global Optimization Problems

2.         A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection

3.               New Modified Controlled Bat Algorithm for Numerical Optimization Problem

 

 

·         Firstly, for section 1, authors should provide more specific comments of the cited papers after introducing each relevant work. What readers require is, by convinced literature review, to understand the clear thinking/consideration why the proposed approach can reach more convinced results. This is the very contribution from authors. In addition, authors also should provide more sufficient critical literature review to indicate the drawbacks of existed approaches, then, well define the main stream of research direction, how did those previous studies perform? Employ which methodologies? Which problem still requires to be solved? Why is the proposed approach suitable to be used to solve the critical problem? We need more convinced literature reviews to indicate clearly the state-of-the-art development.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

1.The coefficient  innovation idea is this paper key point, but the author did not write down the criteria and method to describe how to delete the service arc(network) and fleet size?

2.What is the "MIP gap"? how to measure the "MIP gap"? The author didn’t define and explain the meaning. How to convinced the readers your algorithm is better than the primal model?

3.The author only release the decision variables from positive integer to positive real number, not add any constraints, that is not new approach of solving integer problems. The paper didn’t show the innovation and power of iterative backbone algorithm in the service network decision variables for the business model applications.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Dear authors, I read your manuscript and appreciate the work. Maybe some of my comments help to improve the work.

Introduction:

The introduction appears to be very short. Can the authors give a bit more context to SND. Please outline to the reader what it is and its importance and challenges. We know shortly from the abstract, but that is not enough.

Is the paper tied  to a specific country? Or to global situation? Can the authors please expand the introduction respectively.

In addition the introduction need to be backed up with appropiate citation. So far there is a total of two references only. Referencing is also needed in order to emphasize the value of your paper. It is fine to indicate the twofold objective of your paper, but it should be in perspective with the recent body of literature. Otherwise it is just claims. 

Literature review:

This is not a literature review. Half of it belongs to the introduction ( lines -66).  Can the authors instead focus more on the mixed interger optimization models and arc based network sturctures and the respective algorithm as indicated in the aim and objectives in the literature review.

Results and discussion

Results are presented but again not put in persepective with any literature. A discussion is completely missing.

Conclusion

Can the authors critically reflect on their overall work and methodological choices. And a limitation section to the study.

Can the authors outline the value of their work and relevance of different stakeholders who benefit from it. Please suggest best practice recommandations

Can the authors provide suggestions for future research

 

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

The paper "An Iterative Backbone Algorithm for Service Network Design Problems" is interesting and within the scope of Processes. I think the content is innovative and never published.

The abstract is

The discussion section is not complete, the reviewer need the authors present the limitation of this study and further consideration including but not limited to above comments.

The novelty should be seriously mentioned in the introduction section, a detailed literature review is required to present the background.

It is not correct numbering with values 1 to 11 both middle-scale and large instances.

Last but not the least, what are the quantitative results from this research? Authors did not present in the abstract and conclusion. This is not smart work. Please consider it.

The structure of the paper should be seriously revised: the authors should move Figure 7 in the Results section; Figure 8 is in the refrence section.

The reference section does not comply with the template of the Journal.

The authors did not use the template (e.g. in the head of the pages).

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

·         Consider the following studies in the reference section:

a)      Constructing Domain Ontology for Alzheimer Disease Using Deep Learning Based Approach

b)      Population Initialization of Seagull Optimization Algorithm with Pseudo Random Numbers for Continous Optimization

c)      Detection Of Fake News Text Classification On Covid-19 Using Deep Learning Approaches

 

 

Reviewer 3 Report

My comments have been considered and thoroughly implemented. I have no more reservation toward the paper.

Reviewer 4 Report

The paper can be accepted.