Solving tsp with ACO (ant colony optimization) in python
using heuristic algorithm to solve high dimensional tsp problem
Cities are included in "Cities List.txt" in repo to add or remove cities you've got to include or exclude cities in every line like: "1 909 649"
First number is city index and next two numbers are city euclidean coordinates: x,y which are set to 0 to 1000 but you can change the range to any range
The distance between cities are calculated by Euclidean Distance which is:
I look forward to you questions about the project!
route found by algorithm at iteration of 16(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 32(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 48(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 64(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 80(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 96(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 112(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 128(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 144(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
route found by algorithm at iteration of 160(feeding algorithm with list of 20 city euclidean coordinates: x,y from 0 to 1000 ):
