A Freight Train Optimized Scheduling Scheme Based on an Improved GJO Algorithm
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe article titled "A Freight Train Optimized Scheduling Scheme based on Improved GJO Algorithm" addresses a relevant and timely issue in the field of freight railway transportation, proposing an optimized scheduling model that combines economic criteria with advanced metaheuristic techniques. The methodological approach, based on a hybrid algorithm (IGJOGA), represents an interesting contribution to the area of logistics optimization and is validated through standard benchmark tests and a practical simulation with real-world data, which reinforces its applicability.
However, the article presents several weaknesses that limit its scientific impact. The English writing is deficient in several sections, with grammatical errors, redundant structures, and inadequate use of technical terms. The theoretical justification for using the improved algorithm could be expanded, especially in comparison to other recent metaheuristics. Moreover, a deeper analysis of the results and their practical interpretation is lacking, as well as a discussion on the model’s scalability and computational feasibility.
In formal terms, formatting issues persist, with incomplete references and unedited template text. Nevertheless, the work has potential if it undergoes a thorough technical and linguistic revision. Its focus is pertinent, and with substantial improvements, it could become a valuable contribution to the literature on railway scheduling and evolutionary optimization.
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Author Response
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Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for Authors- Title: Suitable;
- Keywords: Suitable;
- Abstract: Suitable;
- Itemization: Correct;
- Text: Clear and objective;
- This article presents a highly interesting topic. The problem to be analyzed is well-defined. The variables to be analyzed are presented. Functions to be optimized are also presented. Practical application of the developed algorithm.
- Figure 3 should be presented in a larger format that allows it to be read.
- References are few in number, there are good European articles on this topic.
- Conclusions consistent with the proposed methodology and application in the case study.
Specific Comments:
The article addresses the study of railway operation optimization, a problem typically of great interest to the technical community. If the authors intend for this article to be read by non-Chinese readers, they need to provide some additional information about the factors studied. Here are a series of questions that may improve understanding of the problem analyzed:
- In mixed traffic conditions between passenger and freight trains, which one has priority when overtaking?
- Are the railways in these rail corridors single, double, or multi-track?
- Do all hubs have multimodal terminals?
- Is there a time window in the network schedule to allow the operation of freight-only trains?
- Is it possible to bypass the mixed train stop at a passenger boarding station?
- What would be the average speed of freight trains?
- If passenger and freight trains have different operating speeds, how does overtaking occur?
- Do the loads analyzed have a single origin and destination or multiple destinations?
- What would be the time impact on passengers in a mixed train?
- Doesn't the delay in forming a new train discourage passengers from using the train? Are high-speed train passengers captive?
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe article is devoted to the optimization of freight train scheduling within the high-speed railway infrastructure of China. This problem is relevant and of practical significance. The paper proposes a mathematical model that takes into account constraints related to stops, load capacity, and costs. The main objective is to maximize economic efficiency.
The study employs an improved hybrid algorithm, IGJOGA, which combines a genetic algorithm with the Golden Jackal Optimizer.
Despite the overall positive impression of the article, in my opinion, it requires substantial revisions.
The authors should provide stronger justification for the novelty of the proposed algorithm in comparison with other hybrid algorithms. It would be appropriate to focus on the authors’ own contribution that distinguishes their approach from previously published results.
In section 5.2, the origin of the data used should be specified.
A sensitivity analysis of the model should be carried out for such parameters as freight volume, costs, etc.
The possibility of scaling the results to larger city networks should be analyzed.
The time required to perform computations using different algorithms should be analyzed, taking into account real-world application scenarios.
Comments on the Quality of English LanguageThe manuscript requires careful English language revision.
Author Response
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Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
Comments and Suggestions for AuthorsThe manuscript addresses an important and practically significant problem — the optimization of freight train schedules within China’s high-speed railway network.
The proposed mathematical model and algorithm demonstrate potential value and applicability.
However, at the current stage, there are several remarks:
The novelty of the proposed hybrid algorithm is insufficiently justified. The authors are advised to make the justification more analytical rather than descriptive, and to provide a deeper critical comparison with analogous approaches.
The justification regarding computational performance should be strengthened, taking into account realistic application scenarios.
Adding a sensitivity analysis would confirm the robustness of the model when parameters change.
Comments on the Quality of English LanguageThe manuscript is generally understandable, but several grammatical and stylistic inaccuracies remain that should be corrected for better academic clarity
Author Response
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Author Response File: Author Response.pdf
Round 3
Reviewer 3 Report
Comments and Suggestions for AuthorsThe manuscript demonstrates some improvements. However, in my opinion, several important issues require further attention before the paper can be considered for publication:
It is advisable to include a more analytical comparison with other hybrid algorithms.
Additional analysis should be conducted under realistic application scenarios.
A sensitivity analysis of the model to changes in key parameters should be performed.
Comments on the Quality of English LanguageA professional proofreading is recommended.
Author Response
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Author Response File: Author Response.pdf
