Meta-Heuristic Solver with Parallel Genetic Algorithm Framework in Airline Crew Scheduling

Round 1

Reviewer 1 Report

 

This paper proposes a new heuristic solver based on Parallel Genetic Algorithm and innovative crew scheduling algorithm, which improves the traditional crew scheduling by integrating into a single problem. That's a great idea, but I still have a few questions:

1. Please normalize the representation of variables in the article. For example,

(1) Whether d_r^k in line 167 corresponds to b_r^k in line 168;

(2) The excess decimal point in Equation (5);

In addition, Reviewer suggests that the variables mentioned in Section 3.1 and their explanations be summarized in Table 1 as well. Moreover, the variables in Table 1 and their meanings should be mentioned in the first place in the article and then summarized into a table. Reviewer wonders if the abbreviation after the variable is related to its interpretation, such as MaxBlk as "maximum duty flight time".

2. In Section 3.2, the authors mention the objective function as Equation (4), which is to maximize n_F. Perhaps I did not notice that  never appears again in the following. So Reviewer could not see clearly the relationship between the objective function and the constraints.

3. Could Figures 6 and 9 be a little clearer?

4.  The data set used in this article comes from a single source. Should we use a better data set?

 

5. In Dataset B, when the number of threads increases, the efficiency decreases. The explanation given is not reflected in Dataset A. The author should give a better reason.

 

Author Response

Dear Referee,

Thank you very much for your review and very helpful and constructive comments. We have carefully revised the manuscript according to your suggestions and addressed the issues raised in your report. For your convenience, enclosed please find the itemized descriptions on how the issues are addressed in attachment.

Thank you and best regards.

Yours sincerely,

Weihao Ouyang and Xiaohong Zhu

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper studies the parallel genetic algorithm in airline crew scheduling problem. The authors proposed a new heuristic solver based on Parallel Genetic Algorithm and innovative crew scheduling algorithm. The detail of the method is provided. 

However, this paper could be improved by details explaination of the experiments. For example:

(1) Why use the index "the ratio of the number of flights after adjusted to the initial number of flights" in Figure 4?

(2) The results is not mean value in Figure 5 and 8.

(3)Why use optimization raition in Figure 6?

 

Author Response

Dear Referee,

Thank you very much for your review and very helpful and constructive comments. We have carefully revised the manuscript according to your suggestions and addressed the issues raised in your report. For your convenience, enclosed please find the itemized descriptions on how the issues are addressed in attachment.

Thank you and best regards.

Yours sincerely,

Weihao Ouyang and Xiaohong Zhu

Author Response File: Author Response.pdf

Reviewer 3 Report

The paper is very technical and detailed, but  aim of the paper is not very clear, tasks of research, clearly described motivation for choice of applied research methods, Conclusions could be more precise formulations of findings of research results.

Author Response

Dear Referee,

Thank you very much for your review and very helpful and constructive comments. We have carefully revised the manuscript according to your suggestions and addressed the issues raised in your report. For your convenience, enclosed please find the itemized descriptions on how the issues are addressed in attachment.

Thank you and best regards.

Yours sincerely,

Weihao Ouyang and Xiaohong Zhu

Author Response File: Author Response.pdf

Reviewer 4 Report

The manuscript in hand is well written, well presented and is correct scientifically and grammatically. In my opinion this manuscript will contribute a lot in the direction of air transport management. I recommend its acceptance after the following minor changes:

1. Title of the manuscript is too short and not appealing, it needs to be addressed./

2. Historical background- is not convincing, it should be rewritten.

3. There are certain references that are incomplete, these should be completed.

4. Write all the references on same pattern.

Author Response

Dear Referee,

Thank you very much for your review and very helpful and constructive comments. We have carefully revised the manuscript according to your suggestions and addressed the issues raised in your report. For your convenience, enclosed please find the itemized descriptions on how the issues are addressed in attachment.

Thank you and best regards.

Yours sincerely,

Weihao Ouyang and Xiaohong Zhu

Author Response File: Author Response.pdf

Reviewer 5 Report

In this paper, the authors propose a new heuristic solver based on Parallel Genetic Algorithm and innovative crew scheduling algorithm, which improves the traditional crew scheduling by integrating into a single problem. The current version can't be accepted.

1. The meaning of GAFT abbreviation in the title is not clear. Has little to do with subsequent words.

2. There are many difficult sentences to understand, for example,' but it is a multi-constrained linear integer programming problem'.

3.What is the meanning of GAFT? 

4. The innovation of the paper is not clear.

5. Literature review is not relevant enough to this research.

6. What are the assumptions of the model?

7. Lack of introduction to the overall framework.

8. Genetic algorithm is the simplest form. Is there any improvement?

9. The algorithm experiment needs to be compared with meta-heuristic algorithm.

Author Response

Dear Referee,

Thank you very much for your review and very helpful and constructive comments. We have carefully revised the manuscript according to your suggestions and addressed the issues raised in your report. For your convenience, enclosed please find the itemized descriptions on how the issues are addressed in attachment.

Thank you and best regards.

Yours sincerely,

Weihao Ouyang and Xiaohong Zhu

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Structure could be performed better.

Reviewer 5 Report

The quality has improved to a great extent. And the current version of the paper can be accepted now. Congratulations!