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System Design & Architecture
Deep Dive Engineering Case Study

Saarthi

Collision-Free Train Path Optimization System

Live Production Source Code Video Demo
Optimization Engine:IBM ILOG CPLEX
Domain:Railway Scheduling & Routing
Hackathon:SIH 2025
IBM ILOG CPLEXOPL (Optimization Programming Language)Operations ResearchReactViteJavaScriptData VisualizationSimulation Modeling
Problem Statement & Business Need

Saarthi is a decision-support system developed during Smart India Hackathon 2025 for the Ministry of Railways. The project focuses on optimal and collision-free train path prediction using Operations Research models implemented with IBM ILOG CPLEX and OPL. The backend optimization engine computes feasible schedules and paths under real-world constraints, while a React-based frontend visualizes simulations and system responses, enabling stakeholders to analyze and validate routing decisions interactively.

High-Level Architecture & Flow

Decoupled client-server topology designed for high availability, low-latency client synchronization, and zero-egress distributed cloud hosting.

Key System Highlights

  • Collision-free train path and schedule optimization
  • Operations Research-based modeling using IBM ILOG CPLEX
  • Constraint-based optimization with OPL
  • Frontend simulation and visualization of routing decisions
  • Designed for real-world railway traffic constraints
  • Built for Smart India Hackathon 2025 - Ministry of Railways problem statement