The Travelling Salesman Problem (TSP) is a complex problem in combinatorial optimization that cannot be solved conventionally particularly when the number of cities increases. The aim of this project is to compare the effect of using two distributed algorithms (popular meta-heuristics techniques used for optimization tasks) which are Ant Colony Optimization (ACO) as a Swarm intelligence algorithm and Genetic Algorithm (GA).

For Ant Colony Optimization, We studied the effect of some parameters on the produced results, these parameters as: number of used ants, maximum tours, and number of cities. On the other hand, We studied the chromosome population, crossover probability, and mutation probability parameters as well as the effect of number of cities, generations and population effect on the Genetic Algorithm results. The comparison between Genetic Algorithm and Ant Colony Optimization is accomplished to state the better one for travelling salesman problem. The results of comparison show that ant colony is better than genetic algorithm and it generally requires only a few lines of code.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

What libraries you need to run the program and how to install them

1. Matplotlib
2. Tkinter
3. pandas
4. numpy

A step by step series of commands that will help your development env running.

Use Python 3.7 :

pip install matplotlib
pip install tkinter
pip install pandas
pip install numpy

Just open your terminal, head to cloned directory, do:

python TSP_ACO_GA.py

Note: /python must be added to your system's Global path

To see the output and comparison ,user can opt two pathways:

1. By clicking on Comparison you can see the comparison of both the algorithms.
2. By Clicking their specific button, you can see their real time graph.

1. [Tkinter] - The GUI Framework
2. [HTML,CSS,JS] - For Deploying

• Bhupesh Parakh - jainbhupesh533
• Twinkle Gupta - Twinkle0799
• Resham Chaney - Resham Chaney
• Heena Rawat - heena1725

• Dr. Aditya Khamparia