This code implements a genetic algorithm-based solver for the Traveling Salesman Problem (TSP). It starts by setting parameters such as the
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This code implements a genetic algorithm-based solver for the Traveling Salesman Problem (TSP). It starts by setting parameters such as the number of cities, the number of generations, population size, mutation rate, and crossover rate. Then, it generates initial city coordinates and population. In each generation, it calculates the fitness of the population, selects the best route, performs selection, crossover, and mutation operations, and updates the population. Finally, it plots the best route. The entire process iteratively optimizes through a genetic algorithm to find the shortest path.
Cite As
CoderK (2026). Genetic algorithm applied to TSP (https://uk.mathworks.com/matlabcentral/fileexchange/169221-genetic-algorithm-applied-to-tsp), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired by: tsp with ga
General Information
- Version 1.0.0 (1.55 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0 |
