A New Stochastic Model for Bus Rapid Transit Scheduling with Uncertainty
, Afshin Asadi 2, Ramin Giahi 3, Ali Tahanpour Ardakani 4 and Ali Azadeh 3Round 1
Reviewer 1 Report
This paper proposes a Mixed Integer Non-Linear Programming model which focuses on BRT scheduling and uses scenarios-based method for solutions. In general, the paper is organized well and easy to follow. The model is straightforward and solution approach is common in stochastic programming. There are several issues that need to be further addressed:
- Some of uncertain parameters must be correlated with each other. For example, the arrival time and departure time of bus i. Thus, they cannot be independent. How are the distributions of these parameters generated?
- If the bus has a full capacity at a stop k, then the passengers in the following stops will remain for the next bus. Is this scenario considered in the model?
- In 2.2 Notation, please clearly present the decision variables.
- Equation (1), is p(s) probability of scenario s? And there omits a bracket “]” the objective function. Please double check the objective.
- Where is the nonlinear term in the model? Please clearly describe in the context.
Author Response
Please see the attached file containing the responses to the comments of reviewer 1, reviewer 2, and Associate Editor.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
All in all, the paper is very weak, and there are many problems, including a weak literature review. The literature of this paper is very old, maybe for at least five years ago, and I can not see any new reference in this paper, while man studies have been conducted in recent years. In addition, the contribution of the model is not stronger. Furthermore, the contribution of the paper is very unclear. While the complexity of the problem is high, a reasonable solution method has not been proposed. Moreover, the computation results and discussion are very below a scientific paper's basic criteria.
Author Response
Please see the attached file containing the responses to the comments of reviewer 1, reviewer 2, and Associate Editor.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The authors made a good revision in a short period. The concerns were addressed.
Author Response
Please kindly find the attached response document.
Author Response File: Author Response.pdf
Reviewer 2 Report
The authors significantly improved the paper. However, some minor corrections are needed. Please remove the space after figure 1. Figure 8 should be revised; it is a bit confusing. A managerial section before the last section is needed to show the practical importance of this research.
Author Response
Please kindly find the attached response document.
Author Response File: Author Response.pdf
