NOAH as an Innovative Tool for Modeling the Use of Suburban Railways

Round 1

Reviewer 1 Report

This paper proposes a new method called Nest Of Apes Heuristic for modeling specific problems by combining technical aspects of transport systems with human decision-making, which is of current interest and clearly presented and relevant to the scope of this journal. The figures and graphs are clear and meaningful. I recommend to accept for publication after minor revision for a small point.

The conclusions seems quite descriptive rather than explanatory and they have an element of triviality within them; I am sure the authors can do something better out of them.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors develop a new heuristic algorithm based on the behaviors of monkey groups, which is termed NOAH (Nest of Apes Heuristic), and two experiments are conducted to demonstrate the newly developed algorithm. Some comments are listed as follows:

1. What are the major advantages of the developed algorithm compared with other heuristic algorithms, such as Genetic Algorithm, Particle Swarm Optimization?

2. Line 164: What behaviors are used in the algorithm?

3. Fig. 1: What are the meanings of the big black spots and the little black spots?

4. Eq. (2): What is the meaning of “i” in Eq. (2)?

5. Line 281: What is defined as the monkey position for the problem in this case study?

6. Eqs. (6-7): Why these two equations can convert the factors to monkey positions? A more detailed explanation is needed.

7. Line 316: Why the number of monkeys is considered 16?

8. Section 4 Application example of NOAH: What are the optimization results of the case using the developed method NOAH?

 

9. Line 428: How the human behavior considered in the developed method? A more detailed explanation is needed to be provided in the introduction of the NOAH.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 3 Report

Interesting topic, but I have failed to understand the model and see the practical application of it. You state to have a list of 16 factors that influence the use of suburban railway. But how to you measure the increase/decrease of use? How can F2 - number of passengers (in trains in a day) or F3 - number of people who get on the train in the chosen stations (one course) can be influence factors? Aren't they the outputs showing the use of suburban rail? Moreover, did you test the correlation between the factors? How do you explain that there is no relation between the number of departures and number of passenger (when the Mohring effect is well documented)? You state: "Several factors and their collections are considered. Among them are new railroads, bus lines and parking lots. These data were confronted with the observed values of the number of passengers, etc." Why did you opt not to go with all these factors, and what "confronted" means?

 

So additional remarks:

Introduction is missing research goals and paper structure. This must be added. English terminology is poor (eg. "by means of "complementary tools or means of transport" " should just "by other transport modes"; not "co-operation" but "intergration"; "number of courses" - do you mean the number of departures?, "number of cars identified on PR" is this the total number of cars using PR (parking volume)?, travel time in the journey with the use of train" is just travel time by train, and similar for other).

In the Chapter 2 you give the table with different heruistics, but you must also add what problems are these used for? Also, the chapter has a strange formatting, different fonts and gray highlighting or something similar?

The concept of NOAH is presented in a good manner. 

The conclusions must be improved, to show the outputs of your research and futher research directions.

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Thank you for the authors’ response. However, I still feel very difficult to suggest acceptance of the manuscript for publication. Comments are listed as follows:

1. How the human behaviours considered? It is still unclear.

2. What is the major advantage of the proposed method compared with other methods?

 

3. How to demonstrate the effectiveness of the proposed method? 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

The manuscript is improved, and important parts are added. Thank you to the Authors for clarifying the purpose of the NOAH method. However, I am not clear with research goals. You did not create a new method, NOAH is already invented, but you have adjusted it and applied to a transport system problem. Therefore, the goal can not be "to create a new algorithm (NOAH) not as an optimization tool but as a method of observation of selected data sets", but maybe to apply NOAH for that purpose. Moreover, I am not sure what you mean by observing and what is the practical applicability of this. The sentance "The reason for this is the problems with the identification of the close set of important factors and with the collection and selection of the data" is unclear. How does NOAH help you to identify the close set of factors? You have selected them and applied NOAH. Can maybe NOAH be used to clear this set a leave the important ones? I don't have the answer on this.

I still have a problem with F2 - number of passengers (in trains in a day) or F3 - number of people who get on the train in the chosen stations (one course) being influence factors. From my point of view, these are parameters showing the usage of suburban railway transport (the more passengers you have in trains and at stations the usage is higher). If you still insist on these being influential factors then I can argue whether these have a positive or negative influence. I'd say negative, since if trains and stations are crowded this could demotivate others to use the railway.

Moreover, F13 - travel time by competitive public transport (in a peak hour) and F14 - travel time by private cars (in a peak hour), I think are positive factors, meaning that the increase in travel time of other modes will make the railway more competitive and thus increase usage. It could be negative if you look at lower values of F13 and F14 decrease the patronage in rail transport. 

You have stated in answers: "The sources for the heuristics collected in table 3 (in chapter 2) are also presented in table 1 and in table 2 in the context of problems for what these are used (chapter 1)." I stronlgy suggest that you aggregate these tables into one table so all important aspects can be analyzed. 

You have stated in answers: "Chapter 2 and the whole manuscript are better formatted now". However, the chapter still has a strange formatting, gray highlighting or something similar. Please fix this.

Conclusion are improved, but still I don't see the how does NOAH help in decision making process, or for correlation analysis of the factors in suburban railway? There is no clear output of your research to backup your statement that NOAH is "the key innovation in analyses of “technical systems” like suburban railways considered here". 

Author Response

I thank the Reviewers and the Editor for showing the weakness of my paper as difficult the understanding the specific elements. I hope that the new version is clear now. I changed some parts of the manuscript (see the word file with the selection of changes). I add the new version in PDF format (without selection of changes) and point-by-point answers to the all remarks of reviewers (the table).

 

Answers to Reviewers’ comments

	Remark	Answer
Reviewer 2
1	How the human behaviours considered? It is still unclear.	I am commenting on it in the enhanced conclusions, especially in rows 420 – 425 The data (describing the transportation systems) depend partially on human decisions. For example choice of the mode of transport could be the reaction to the behaviors of other people (neighbors, social media groups). So, an individual can observe and copy the leaders as a follower. The use of the specific transport means influencing the number of passengers or parking volume on PR has some uncertainties and could be modeled using heuristics.
2	What is the major advantage of the proposed method compared with other methods?	I am commenting on it in the enhanced conclusions, especially in rows 418 – 420 and in 436 – 439 The main advantage of the proposed method is the creation of the possibility to observe various sets of data and their interactions without precise knowledge about the influencing of the specific factor for the result. (…) The strict comparison of this new method with others is not possible because of other goals of them. The heuristics search mainly for optimal solutions. NOAH can compare factors not showing the best result. This is an intentional assumption representing the difficulty of evaluation of data by an individual person.
3	How to demonstrate the effectiveness of the proposed method?	I am commenting on it in the enhanced conclusions, especially in rows 439 – 444 So the evaluation of the effectiveness of the proposed method is difficult, especially in the present stage of research. The study introduced in one of the Polish agglomerations will be continued and should formulate the remarks to modify the selected elements of the transport system (eg. number of departures or cost) with the observation of changes in other factors. When the obtained results will be similar to the model, then NOAH will be effective.
Reviewer 3
4	The manuscript is improved, and important parts are added. Thank you to the Authors for clarifying the purpose of the NOAH method. However, I am not clear with research goals. You did not create a new method, NOAH is already invented, but you have adjusted it and applied to a transport system problem. Therefore, the goal can not be "to create a new algorithm (NOAH) not as an optimization tool but as a method of observation of selected data sets", but maybe to apply NOAH for that purpose.	NOAH is my own idea. I created it when analyzing the data described the railway system and when study different heuristic. Now I write about this in selected parts of the paper (eg. 89, 90), especially in conclusions: This method (…) is quite similar to swarm intelligence algorithms (like PSO, ACO) but contains new elements based on the specific behaviors of monkeys described in section 3. (rows 432 – 435). The algorithm is not presented and published previously. I don’t know all published heuristics, but the creation of the same method (with its name and procedures) by another Author is not possible.
5	Moreover, I am not sure what you mean by observing and what is the practical applicability of this. The sentence "The reason for this is the problems with the identification of the close set of important factors and with the collection and selection of the data" is unclear. How does NOAH help you to identify the close set of factors? You have selected them and applied NOAH. Can maybe NOAH be used to clear this set a leave the important ones? I don't have the answer on this.	I change some elements in selected parts of paper, especially in rows 191 – 192 Initially, the selection of parameters is made by an “expert” with the use of all of the available data. I comment this question also in the conclusions (rows 437 – 439) The heuristics search mainly for optimal solutions. NOAH can compare factors not showing the best result. This is an intentional assumption representing the difficulty of evaluation of data by an individual person.
6	I still have a problem with F2 - number of passengers (in trains in a day) or F3 - number of people who get on the train in the chosen stations (one course) being influence factors. From my point of view, these are parameters showing the usage of suburban railway transport (the more passengers you have in trains and at stations the usage is higher). If you still insist on these being influential factors then I can argue whether these have a positive or negative influence. I'd say negative, since if trains and stations are crowded this could demotivate others to use the railway.	I commented on this aspect in rows 280 - 286 This is a proposal used in this research considering specific assumptions (not defining the close set of factors and their role). For example, factors F2 and F3 are classified as “positive” according to an assumption of the offer presented by the rail operator with a higher number of places than forecasted demand. In such an assumption, the trains will not overcrowded. The higher number of passengers or people who get on the train will increase the use of suburban rail because of the creation of “good behavior” for new passengers.
7	Moreover, F13 - travel time by competitive public transport (in a peak hour) and F14 - travel time by private cars (in a peak hour), I think are positive factors, meaning that the increase in travel time of other modes will make the railway more competitive and thus increase usage. It could be negative if you look at lower values of F13 and F14 decrease the patronage in rail transport.	I re-define the sense of “positive” and “negative” factors (rows 278 – 280) Rising values of positive factors increase the total number of travelers (in all modes), and increasing values of negative factors reduce this number.
8	You have stated in answers: "The sources for the heuristics collected in table 3 (in chapter 2) are also presented in table 1 and in table 2 in the context of problems for what these are used (chapter 1)." I strongly suggest that you aggregate these tables into one table so all important aspects can be analyzed.	I connected tables 1 – 3 and changed the descriptions.
9	You have stated in answers: "Chapter 2 and the whole manuscript are better formatted now". However, the chapter still has a strange formatting, gray highlighting or something similar. Please fix this.	I am very sorry, but on all of my computers, the whole of chapter 2 looks good. Please see the attached PDF version. Perhaps is it the problem with the version of Word?
10	Conclusion are improved, but still I don't see the how does NOAH help in decision making process, or for correlation analysis of the factors in suburban railway? There is no clear output of your research to backup your statement that NOAH is "the key innovation in analyses of “technical systems” like suburban railways considered here".	I improved the description of the assumptions of the new method (rows 139 – 144) So, the new model (algorithm) should be allowed to compare different data with higher or lower complexity to show potential sets of them. It will be possible to analyze both the existing (observed) data as well as more theoretical values of them. The process of comparison should be flexible and based on partially random procedures. The assumptions collected above can be realized using a specific heuristic. The novel heuristic will be proposed based on the specific behaviors of monkeys. This aspect is also commented in the conclusions (rows 418 – 425 and 436 – 444) The main advantage of the proposed method is the creation of the possibility to observe various sets of data and their interactions without precise knowledge about the influencing of the specific factor for the result. The data (describing the transportation systems) depend partially on human decisions. For example choice of the mode of transport could be the reaction to the behaviors of other people (neighbors, social media groups). So, an individual can observe and copy the leaders as a follower. The use of the specific transport means influencing the number of passengers or parking volume on PR has some uncertainties and could be modeled using heuristics. (…) The strict comparison of this new method with others is not possible because of other goals of them. The heuristics search mainly for optimal solutions. NOAH can compare factors not showing the best result. This is an intentional assumption representing the difficulty of evaluation of data by an individual person. So the evaluation of the effectiveness of the proposed method is difficult, especially in the present stage of research. The study introduced in one of the Polish agglomerations will be continued and should formulate the remarks to modify the selected elements of the transport system (eg. number of departures or cost) with the observation of changes in other factors. When the obtained results will be similar to the model, then NOAH will be effective.

Author Response File: Author Response.pdf

Round 3

Reviewer 2 Report

Thanks for the authors’ response. The contribution of this manuscript is still unclear. It is suggested that the authors improve the proposed method in further studies. For example, the authors said that the proposed method can observe various sets of data and their interactions. However, in the case study of this manuscript, what interactions of the data sets are still unclear. Moreover, in this study, human behaviors are considered through the data. However, in my opinion, if it is said human behaviors are considered, they should be embedded into the algorithm and affect the results. 

Reviewer 3 Report

Thank you for improving the paper. I apologize for making a remark regarding NOAH method, I understand now that it was developed by you, although I am still not sure if "observation of selected data sets" is the best application of this method and what is the practical importance of it. Moreover, I am also not clear about the effectiveness of the method since it was not presented in the results of its application on the data set used in this research. Anyhow, I will not argue further, let's see what the academic population will say. 

P.S. Formatting is still not good, in PDF file, so it is not due to compatibility issues. Please check it again.