Finding the most efficient flight route between cities can be difficult due to factors such as layovers, travel time, airline availability, and cost. Traditional flight search tools often present large amounts of data without optimizing results based on user preferences. This project uses MeTTa and pathfinding algorithms to compute the best possible flight routes while balancing key criteria such as total duration, distance, and layover efficiency.
- Determine the Shortest Travel Time: Calculate the fastest possible route between two cities by minimizing overall travel duration, including layover times.
- Layover Optimization: Analyze airline schedules to ensure smooth and time-efficient connections.
- Real-World Data Integration: Use airline route datasets to provide accurate and up-to-date recommendations.
- Optimized Pathfinding: Apply algorithms such as Dijkstra’s, A\*, or other suitable approaches to compute the most efficient travel paths.
- Optimized Pathfinding: Computes the most efficient flight routes using Dijkstra’s, A\*, or alternative algorithms.
- Custom Weighting: Allows users to prioritize factors such as travel time, price, distance, or number of layovers.
- Real-World Data Integration: Incorporates actual airline route data to produce accurate and dynamic flight recommendations.
- User-Friendly Input: Lets users specify departure and destination cities with optional filtering and preference settings.