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Special trains are unscheduled trains run to meet the unexpected surge in demand during holidays and festive seasons, which is generally difficult to predict. Special trains were therefore allocated at SCR using rule-based processes, resulting in suboptimal revenues and occupancy rates. This case presents a data-driven approach to schedule special trains based on passenger waitlist data and application of statistical techniques.
The central objectives of the case are the following:
- Understand the limitations of legacy systems and how to overcome them using the latest technologies.
- Discuss the practical approach to solving real-world problems using data analytics in the context of the special train scheduling challenge faced by IR.
- Appreciate the power of data-driven decision support systems and get hands-on experience of building and testing analytical data models.