Public Transport Planning Using Modified Ant Colony Optimization

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper presents a well-structured study of public transport planning using a modified ant colony optimization approach. The methodology is clearly explained and the proposed modifications to COA are well justified, demonstrating practical improvements in route optimization. The case study on the Wrocław streetcar network effectively validates the approach.
Minor revisions could improve the clarity and impact of the paper:
- Provide a brief discussion of the computational complexity of the modified COA compared to the standard version.
- Ensure that all equations and variables are clearly defined, as some notations could benefit from further clarification, particularly in equations (7) and (8).
- A brief discussion of the computational complexity of the modified version of ACO compared to the standard version could be useful to better appreciate the practical implications of the algorithm.
- It would be interesting to explain in more detail the choice of values for the algorithm's parameters (e.g. evaporation and pheromone coefficients).
- Minor proofreading is recommended to improve the readability of certain sections.
- Ensure that figure and table legends are self-explanatory and clearly referenced in the text.
- A short discussion of the advantages and limitations of the approach compared with other heuristic methods could strengthen the scope of the conclusions.
Overall, the paper makes a valuable contribution to sustainable transport planning and can be accepted with minor revisions.

Author Response

Thank you for your feedback. Please find the answers in the annex

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The authors presented a study on public transport route planning using a modified Ant Colony Optimization (ACO) algorithm. The proposed methodology aimed to improve transport sustainability by optimizing routes based on an "effort function" incorporating parameters such as travel time, route length, delays, and attractiveness. The authors claimed that their approach reduces the effort required for public transport routing by 11.5% compared to the current route in Wrocław's tramway network. They conclude that their modification of ACO contributes to sustainable transport planning and can be applied broadly. In my opinion, although the topic is interesting, there are major points that should be addressed before making final decisions.

• First of all, ACO is much used for the specified problem where this manuscript failed to state clearly any significant innovation beyond what has already been published in the literature.
• A proper comparison with state-of-the-art methodologies is necessary, including metaheuristic techniques beyond ACO.
• The authors need to perform a sensitivity analysis to demonstrate how different parameters impact the optimization. Additionally, they should justify the weight assignments in the objective function using real-world data.
• The authors must explicitly define the dataset, its origin, and preprocessing methods. They should also test the algorithm under realistic transport scenarios, including variability in demand and disruptions.
• State of art is weak, studies in transit route planning is not reviewed as in :” Complete hierarchical multi-objective genetic algorithm for transit network design problem”, “Multi-objective transit route network design as set covering problem” and “Integrating underground line design with existing public transportation systems to increase transit network connectivity: Case study in Greater Cairo”.

• The abstract and introduction are cluttered with redundant statements.
• The notation in the mathematical formulations is inconsistent and difficult to follow.

Comments on the Quality of English Language

None.

Author Response

Thank you for your feedback. Please find the answers in the annex

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

1. The specific ways in which the objective function can be modified could be described in more detail, in particular how the weights of the different parameters are determined and how conflicts between these parameters are handled。
2. The experimental results section needs to be analyzed in more detail and more information should be provided on how the method performs under different conditions. In addition, there could be a discussion on whether there are potential factors that could affect the results.
3. Enhance the literature review section by reviewing the classical methods relevant to this study.

Comments on the Quality of English Language

1. Some minor grammatical errors need to be noted, especially the use of connectives in compound sentences.
2. Transitions between certain paragraphs could be strengthened to avoid jumps in expression, especially if the links between different parts are not strong enough.
3. Please recheck for spelling errors and regularity in the use of punctuation, especially in longer sentences where commas and periods should be used more regularly.

Author Response

Thank you for your feedback. Please find the answers in the annex

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have addressed all my concerns.