Ant Colony Optimization for Traveling Salesman Problem
Explore the implementation of Ant Colony Optimization (ACO) to find the optimal route for the Traveling Salesman Problem with a varying number of cities and ants. Visualize the search process in 2D and recalibrate pheromones for efficient results.
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Presentation Transcript
Biologically inspired algorithms Exercise 8 Ing. Lenka Skanderov , Ph. D. 20/03/25 1 text
Content Ant Colony Optimization text 20/03/25 2
Task Implement Ant Colony Optimization (ACO) Use ACO to find out the optimal rout of Travelling Salesman Number of cities: 20 40 Number of ants: 20 40 based on the number of cities Positions of ants: Each ant occupies a different starting position (city) Remember: Pheromones are recalculated at the end of a migration loop Visualize the process of search (in 2D) the same visualization as in the case of the GA text 20/03/25 3
Thank you for your attention Ing. Lenka Skanderov , Ph.D. EA 407 +420 597 325 967 lenka.skanderova@vsb.cz homel.vsb.cz/~ska206 text 20/03/25 4
