Evolutionary Algorithms Traveling Salesman Problem

This is the Evolutionairy Algorithm Demo for the Traveling Salesman Problem that I use to demo the simplicity and power of Evolutionairy Algoritms.

To get it, just clone this repository by using your favorite git gui or by executing

git clone https://github.com/bknopper/TSPEvolutionaryAlgorithmsDemo.git

DISCLAIMER

This is a demo, and as such, I've used the prototyping approach. The domain part of the backend has been constructed with thought...all else was built to work. As fast as possible.

Running the Demo - Backend

Because this demo uses Gradle as package manager / build automation system and has the Gradle wrapper incorporated you can run the backend of this demo by simply executing the gradle wrapper.

For example, from the TSPEADemo directory, run:

./gradlew run

This should start resolving all the dependency and start the backend of the demo for you using Spring Boot.

Running the Demo - Frontend

Since the frontend is based on angular, we need some form of http serving. My favorite is the python SimpleHttpServer and you can let it start serving by running the following from the TSPEADemo/frontend/app dir.

For Python 2:

python -m SimpleHTTPServer 8001

For Python 3:

python -m http.server 8001

Storing runs using Firebase

If you have a Firebase account and would like to store runs and show the 10 latest best, you can add a demo.properties file in the frontend/app dir with the following content:

{
  "useFirebase": true,
  "firebaseURL": "https://yoururlhere.firebaseio.com/algorithmResults"
}

Have fun!

That's it! Now you can navigate to http://localhost:8001 to start playing.

Have fun!

For the talk I did on J-Fall where this demo is used, see: Evolutionairy Algorithms J-Fall talk