An Integrated Model of Train Re-Scheduling and Control for High-Speed Railway
Round 1
Reviewer 1 Report
"We can see that the operational plan and the controlling plan have a significant close connection, interacting with each other greatly." referring to Figure 1., but as shown on Figure 1/ link between “Operational” and “Controlling” plans is presented as unidirectional not bidirectional which is not quite consistent with the forementioned sentence and somewhat confusing suggesting certain “special” type of connection which is not shown on Figure 1. Since whole Figure 1. represents process schematics there is no need to specifically label connection between those two plans as it doesn’t differ from connections from other plans.
On page 9 abbreviations "EMU" and "CRH3" should be explained.
Difference between G and D types of trains should be explained.
Page 18 is completely empty.
A small subjective digression regarding future research - although energy consumption reduction is definitely one of the most discussed topics in the modern world it would be interesting to observe it - optimize as function of time - especially in the segment of passenger trains where optimal timing is a prerogative.
Author Response
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Reviewer 2 Report
Overall reading this paper was a delight to read. Although the presented results demonstrate the operational efficiency gains from rail rescheduling and reliability. I am just wondering how the authors can make a case in incorporating demand constraints and interplay with other modes of transport when applicable to passenger travel related to on-road congestion, just-in-time arrival of passenger and schedule synchronization with other public transit. Finally it might be worthwhile for the authors to demonstrate some results from scenario and sensitivity analyses.
Author Response
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Reviewer 3 Report
- Equations (21), (22), and (23) are hard to read.
- Tables 2,3,4, and 5 should be refined more better.
Author Response
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Reviewer 4 Report
The authors build an integrated model to solve train re-scheduling and train control problem synthetically, which is divided into two stages. The first stage is train re-scheduling, determining the arrival and departure time for trains. Depending on the arrival and departure time, the train running time can be calculated out and it is set to be the constraint of the train control model. The goal of the second stage model is to save tracking energy in train operation process, determining the traction plan in each segment of a section between two stations. The authors also design a quantum-inspired particle swarm optimization algorithm to solve the integrated model. A computation case is presented to prove the effectiveness of the model and the efficiency of the algorithm.
Author Response
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Round 2
Reviewer 2 Report
The revisions address the concerns raised from my previous comments.
