https://github.com/thomasnield/traveling_salesman_demo

A Kotlin implementation of the TSP problem, with TornadoFX Visualization
https://github.com/thomasnield/traveling_salesman_demo

javafx kotlin optimization traveling-salesman-problem

Last synced: 2 months ago
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A Kotlin implementation of the TSP problem, with TornadoFX Visualization

• Host: GitHub
• URL: https://github.com/thomasnield/traveling_salesman_demo
• Owner: thomasnield
• License: apache-2.0
• Created: 2018-06-10T13:07:11.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-06-26T17:43:34.000Z (over 5 years ago)
• Last Synced: 2024-01-30T01:18:53.163Z (11 months ago)
• Topics: javafx, kotlin, optimization, traveling-salesman-problem
• Language: Kotlin
• Homepage:
• Size: 9.94 MB
• Stars: 60
• Watchers: 6
• Forks: 25
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Traveling Salesman Demo

### Built with JavaFX/TornadoFX and Kotlin

This is a Kotlin application (built with [TornadoFX](https://github.com/edvin/tornadofx) visuals) to demonstrate multiple algorithms to solve the [Traveling Salesman Problem](https://en.wikipedia.org/wiki/Travelling_salesman_problem). 

I found this problem interesting due to its simple objective, and yet astronomically large permutations (60 cities = more tour combinations than there are atoms in the universe) that must be pruned and searched through. 

**Current Algorithms**

* RANDOM

* GREEDY

* OVERLAP ELIMINATION

* 2-OPT

* SIMULATED ANNEALING

## YouTube Walkthrough

[![](https://img.youtube.com/vi/j1s69yf4a9Y/hqdefault.jpg)](https://youtu.be/j1s69yf4a9Y)

## Featured at KotlinConf 2018 in Amsterdam

[![](https://img.youtube.com/vi/-zTqtEcnM7A/hqdefault.jpg)](https://youtu.be/-zTqtEcnM7A)