UHAlean's mass transportation solution is based on operations research models, machine learning
algorithms, and advanced optimization algorithms. It uses efficient data management and intelligent
analysis, real-time dynamic analysis, intelligent integrated scheduling, and assists enterprises in
strengthening their decision-making and enhancing efficiency.
Business pain points faced by Mass Transportation
High cost of crew pairing and low utilization
Poor balance and too many steps of scheduling
Inflexible calibration and low efficiency
Difficult to predict, too many conditions
High impact of human error
Disconnected system
Sloppy resource scheduling
Blurred task boundaries
Isolated and scattered data
Algorithm analysis
Airline flight optimization
Daily work efficiency improvement
Closed-loop business process management
Information Integration
Separation of qualification management and handling
