Hybrid Flow-Shop Scheduling Problems with Missing and Re-Entrant Operations Considering Process Scheduling and Production of Energy Consumption
Round 1
Reviewer 1 Report
The topic is not related to the journal scope. And the contents of the paper is mainly about GA algorithm for a machine scheduling problem, the energy consumption is not related to the speed or the missing or the reentrant operations of the scheduling problem. Besides, the paper just combines two objectives into one by adding two arbitrary weights, which is unacceptable. The dual-population GA is not an ideal algorithm to handle bi-objective optimization problem, even if the problem does not concern with the energy topic whatsoever. Furthermore, no sustainability related conclusions or analysis can be found in the paper.
Needs extensive language editing.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Dear respected authors,
1. The aim of the study has been reflected well in the Abstract section.
2. The content of the Introduction section should be supported by more references. There are some definitions, information, etc., like the first and fourth paragraphs, without being referred to a study. Moreover, before the last paragraph of this section, the literature studies should be concluded and the research gap and the significance of the study should be highlighted.
3. In the second section, it should be mentioned that the problem is created for the first time or it is cover by some studies in the past. Because if the latter one is correct, the definitions and assumptions need to be referenced.
4. Section 3 suffers from lack of referencing too. In addition, the difference between the original GA and the improved one should be discussed and the pros and cons of the proposed method should be mentioned. The following study may be useful for the authors to improve the content of this section.
· Ghadiri Nejad, M., Shavarani, S. M., Vizvári, B., & Barenji, R. V. (2018). Trade-off between process scheduling and production cost in cyclic flexible robotic cells. The International Journal of Advanced Manufacturing Technology, 96, 1081-1091.
5. The reason of selecting α1= 0.6, and a2 = 0.4 should be explained. If they have been taken from a similar study, it should be mentioned too.
6. The limitations of the study should be highlighted in the Conclusion section.
Minor English editing is needed for this study.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
1. Rewrite the abstract. As of now, it does not motivate a potential reader. Add some numerical results.
2. The paper needs careful language editing.
3. Modify the title by including the objectives. 4. "there are several hybrid flow shops in engineering that contain both re-entrant and missing operations" - Is this your own statement? If yes, give some examples. Otherwise, provide references. 5. Please include the research gap. 6. Operations can be ignored - Explain this. 7. The following literature papers may be included: - A memetic algorithm to solve uncertain energy-efficient flow shop scheduling problems - Hybrid monkey search algorithm for flow shop scheduling problem under makespan and total flow time8. Explain the constraints clearly. 9. improved two-population genetic algorithm (IDPGA) - Please check this. 10. Please explain the GA shortly and then illustrate your proposed algorithm. 11. What is the stopping criterion of your proposed algorithm? 12. Optimization rate relative to GA - What is this? Explain. 13. How did you take the parameters of the ACO and PSO? From the literature? Explain. 14. There are several recently developed algorithms available in the literature. If possible make more comparisons. 15. What are the limitations of your study? Include in the conclusions section.
The paper needs careful language editing.
Author Response
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Author Response File: Author Response.pdf
Reviewer 4 Report
The reviewed manuscript is well prepared. The authors clearly present the own hybrid flow shop scheduling model with missing and re-entrant operations, which minimize the maximum completion time and reduce energy consumption. The authors propose dual-population genetic algorithm with a three-layer gene coding method, hierarchical crossover and mutation techniques, and also an adaptive operator that considers gene similarity and chromosome fitness values. The proposed algorithm outperformed the other methods (GA, ACO and PSO) in solving production problems and show a higher level of robustness. It was confirmed by the presented practical example.
This manuscript contains well prepared introduction, problem description, mathematical model, experimental analysis and conclusions.
Overall, the article is well edited. I have two comments:
- on line 124 the full name of the IDPGA shortening is incorrect - there is “improved two-population genetic algorithm”, it should be “improved dual-population genetic algorithm”,
- on line 450 is that “IDPGA outperformed the other four algorithms…”, but IDPGA was only compared with three algorithms.
In my opinion, the manuscript’s strengths are:
- the content - attempt to integrate the two methods (RHFS and HFSMO) and design of an improved dual-population genetic algorithm (IDPGA);
- the reviewed manuscript deals with current scheduling problems in production;
- the reviewed manuscript correspond to the subject matter of the journal (Sustainability).
I recommend this manuscript for publication after editorial correction.
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
No comment.
Could be improved.
Reviewer 2 Report
Dear Respected Authors,
The manuscript's content has been modified according to what the reviewer recommended. All the comments and suggestions of the reviewer have been met. According to the reviewer's point of view, the manuscript is worth publishing in the respected journal of Sustainability.
Reviewer 3 Report
Congratulations. The quality of the paper has increased now.
