fatOrange/cuda-TSP-ant-colony-optimisation

This consists of the solution for the Travelling Salesman Problem using Ant Colony Optimization implemented both serially and parallelly in CUDA

Travel Salesman Problem using Ant Colony Optimization

shiva swaroop. v(16CO252)

sri charan. M(16CO228)

Instructions for TSP using ACO ==> Ant Colony Optimization.

• For ACO , since it's a much smaller and simpler code , We just used 1 file each for parallel and CUDA version. we are using an open source map_generator (coded in ruby), that takes the number of cities as a parameter and builds a map.txt that contains a random city map with said N cities. Command to run the map generator : ruby map_generator.rb Num_of_cities

• We have compiled and saved 3 different variants of maps for the ease of the grader to check my code. map25.txt , map50.txt , and map100.txt contains maps with 25,50,100 cities respectively.

• To run the sequential and parallel version of the code.

Just do a 'make'

and to run the sequential version using

for example to run for 25 cities -> ./tsp-ant-cpu < map100.txt

and to run the parallel version using

for example 25 cities -> ./tsp-ant-gpu < map100.txt

This ensures that the input data for parallel and sequential version is same

NOTE: To play around with a number of cities, just open ants.c - line 7 & parallel_ants.cu - line 8and change the #define cities 25 , to whatever value you want ,25,50 or 100 and do a 'make' to compile the code. Since all the memory allocation and some other global variables depend on the 'CITIES' variable, I didn't take it as a parameter and instead defined it as a #define.