Application and Mathematical Analysis of TSP-based Delivery Route Optimization using Greedy, Random, Held-Karp, Simulated Annealing, Branch and Bound, and Nearest Insertion.
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Solve the Traveling Salesman Problem (TSP)
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Compare multiple optimization algorithms:
- Greedy
- Random Search
- Held-Karp Dynamic Programming
- Simulated Annealing
- Branch and Bound
- Nearest Insertion
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Route visualization on an interactive graph
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Performance comparison between algorithms
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Mathematical analysis of route optimization
- Download and extract
TSP_System.zip - Run the executable file
- Select an algorithm
- Generate locations and start optimization
Description: Main application window displaying generated cities, route visualization, and algorithm controls.
Description: Visualization of the optimized delivery route generated by the selected algorithm.
Description: Comparison of route distance and execution time between optimization algorithms.
- Qt Documentation — https://doc.qt.io
- Qt Widgets Overview — https://doc.qt.io/qt-6/qtwidgets-index.html
- QGraphicsView Documentation — https://doc.qt.io/qt-6/qgraphicsview.html
MIT License