The Optimization Model of Ride-Sharing Route for Ride Hailing Considering Both System Optimization and User Fairness

Round 1

Reviewer 1 Report

The paper proposes a optimization model of ride-sharing route for ride hailing. The following changes are adviced to make the paper suitable for publication in "Suistainability":

1- How could the current sanitary situation be introduced into the proposed methodologies? Please address this issue

2- Page 3: The authors state "The principle of system algorithms and user fairness is rarely considered in the modeling". Has been the concepts of system optimization and user fairness previously studied in the literature? If so please include the references and the differences with the presented work .

3-State clearly why is important to fill the gap presented in this paper.

4- Introduction, explain the structure of the paper at the end of this section.

5- Optimization problem: Present a table summarizing where the assumptions and methods considered in this work were previously considered.

6- Why were the genetic algorithms used instead of other heuristic tools?

7-How were the papameters of the genetic algorithm calibrated? the use of orthogonal arrays of Taguchi is advided (see the paper "Calibration of the descent local search algorithm parameters using orthogonal arrays" published recently in Computer-Aided Civil and Infrastructure Engineering). 

8- Include more information about the results of the survey indicated in page 9. 

9- Include details about the calculation time of the optimization algorithm

10-improve the quality of Figure 3. 

11-Why are some parts of the text in blue?

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

In modern realities, road jams are an increasing problem both in megalopolises and in small cities. Taking into account the harmfulness of using a car, the optimization of trips for more than one passenger is a hot topic of discussion and can be a solution to this and many other city problems. For this reason, a large number of high-quality articles is required on this problem. The article is well-written, however further adjustments is required, in particular:

1. In the conclusion, you that “the scale of the road network and the scale of ride-sharing demand in the case study are both small.” It would be nice to know how the computation time changes with increased scales, in other words, what is the computational complexity of the algorithm?

2. What is the scatter of the limit values of the functions in Fig. 3? How much will the average limit value increase or decrease with more runs?

3. Table 3 requires an explanation of the meanings of the arrows for easier reading of the table.

4. It would be a good idea to add a column to Table 4, which represents some analogue of the fuel cost for all trips, to fully understand the difference in the cost of a trip for the driver.

5. The majority of references are modern articles, which indicates that this project is keeping up with the times and optimized for modern realities, however, we would recommend that you refer to a large number of general sources for such an important research.

6. Heading 4. Genetic Algorithm is at the bottom of the page. It is required to transfer it to the next page.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The suggested comments were properly introduced into the paper and it is now suitable for publication. 

Author Response

According to the opinions of the academic editor of Sustainability, we have supplemented the way to obtain the position of the demand point in this case and the position of the paper in the sustainability field, and added three references.