Search

During the year 2020, Indian Railways undertook an extensive timetabling exercise for its entire network. The timetable for its six principal routes known as the golden quadrilateral + diagonals (GQD) was generated using a rail traffic simulation tool. The simulation tool and the methodology had to be customized to handle the complex technical requirements of the GQD network, which spans more than 9,000 km. Challenges related to using and integrating data into the simulator also had to be addressed. This was the first time that a simulation software tool of this kind was used for timetabling in Indian Railways, and hence, there were uncertainties regarding the timely delivery, which gave rise to additional challenges to the overall effort. This paper focuses on these challenges and the managerial and human aspects of this massive timetabling exercise. It also explains how this project leverages the benefits of combining top-down and bottom-up approaches in timetabling and how it sets a new paradigm for network-wide timetabling in Indian Railways. [ABSTRACT FROM AUTHOR]

In this paper, we discuss a model to allocate train capacity among multiple travel segments on an Indian Railways train route with several stops. We use a linear programming model and data preprocessing and postprocessing to determine the optimal capacity allocation on multiple travel legs. The model uses a simple, effective capacity management tool. For historical and social reasons, Indian Railways splits its train capacity based on user and type of travel. Determining the optimal split of such capacity is nontrivial. We deal with the specific issue of the spatial split of seats in an end-to-end travel segment within a given travel class. This addresses the needs of end-to-end and en route travelers. When we applied our model to 17 Indian Railways trains, we achieved increases of 2.6 to 29.3 percent in revenue, 6.7 to 30.8 percent in load factors, and 8.4 to 29 percent in passengers carried. [ABSTRACT FROM AUTHOR]

Abstract: Revenue management is widely practiced in the transport industry, but the bulk of the published literature deals with the airline industry. We consider the case of passenger services in the premium segment of Indian Railways (IR) and illustrate an application of the principles of revenue management. The strategy of overbooking is interpreted in terms of waitlist management by IR and cancellation action of customers. An attempt is made to derive elasticity estimates between key mode choices internal to the railways and finally, revenue management through differential pricing is suggested as a means to increase revenue on average. [Copyright &y& Elsevier]