Ant-Q-KGA

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ACO with RL algorithm integration (Q-learning) and k-means boosted genetic applied to TSP

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<h3 align = "center">An hybrid metaheuristic approach</h4> 
<h6 align = "center">to the travelling salesman problem</h6>

<a href="#content">Content &nbsp;</a> |
 <a href="#structure">&nbsp; Repo Structure &nbsp;</a> |
 <a href="#datasets">&nbsp; Datasets per test performances &nbsp;</a> |
 <a href="#aboutus">&nbsp; About us &nbsp;</a>

<a name="content"></a>
## &#9741; &nbsp; Content
ACO with RL algorithm integration (Q-learning)

Genetic algorithm scaled with k-means clustering

Applied to symmetric Travelling Salesman Problem

<a name="structure"></a>
## &#9741; &nbsp; Repo Structure
Folders:

 
 - [**Sequential_ACO**](https://github.com/DBertazioli/Ant-Q-KGA/tree/master/Sequential_ACO) contains the sequential ACO implementation, used as an internal reference while developing the parallel algorithm. No results among those produced in the report belongs to such an implementation.

- [**genomic**](https://github.com/DBertazioli/Ant-Q-KGA/tree/master/genomic) contains out implementation of the genomic algorithm, along with the hybrid approach.
 
 - [**parallel-ACO**](https://github.com/DBertazioli/Ant-Q-KGA/tree/master/parallel-ACO) contains the parallel implementation of Ant Colony Algorithm in Python.
 
 - [**parallel-AntQ**](https://github.com/DBertazioli/Ant-Q-KGA/tree/master/parallel-AntQ) contains the parallel implementation of Ant-Q Algorithm in Python.
 
 - [**presentation**](https://github.com/DBertazioli/Ant-Q-KGA/tree/master/presentation) is a section under developement (spoiler alert: should contain the presentation slides!)
 
 - [**report**](https://github.com/DBertazioli/Ant-Q-KGA/tree/master/report) contains the project repo along with its latex source code.

<a name="datasets"></a>
## &#9741; &nbsp; Datasets for test performances

- [dj38](http://www.math.uwaterloo.ca/tsp/world/dj38.tsp) 
- [berlin52](http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsp/berlin52.tsp) 
- [ch130](http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsp/ch130.tsp) 
- [d198](http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsp/d198.tsp) 
- [pr1002](http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsp/pr1002.tsp)

<a name="aboutus"></a>
## &#9741; &nbsp; About us

&#8860; &nbsp; **Dario Bertazioli**

- *Cosa studio*: Studente Magistrale di Data Science presso l'Università degli Studi di Milano-Bicocca;
- *Studi precedenti*: Laurea triennale in Fisica presso l'Università degli Studi di Milano.

&#8860; &nbsp; **Fabrizio D'Intinosante**

- *Cosa studio*: Studente Magistrale di Data Science presso l'Università degli Studi di Milano-Bicocca;
- *Studi precedenti*: Laurea triennale in Economia e Statistica per le organizzazioni presso l'Università degli Studi di Torino.

&#8860; &nbsp; **Massimiliano Perletti**

- *Cosa studio*: Studente Magistrale di Data Science presso l'Università degli Studi di Milano-Bicocca;
- *Studi precedenti*: Laurea triennale in Ingegneria dei materiali e delle nano-tecnologie presso il Politecnico di Milano.

Ant-Q-KGA

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