Parallel Evolutionary Algorithm which tackles the problem of assigning routes to garbage trucks for picking up every garbage container with certain restrictions while trying to minimize time and distance of the routes. Final project of Evolutionary Algorithms course - UDELAR.
Using public available data from Uruguay's public datasets on the location of garbage containers in the city of Montevideo. We've tackled the problem of assigning routes to garbage trucks with certain restrictions. Therefore we elaborated an original time/distance matrix dataset of all Montevideo garbage containers which has been uploaded to Figshare.
Below you can find a report about the algorithm (Explanation, experimental analysis and performance reports) and its source code. You can also find the source code on Github.
This project was a great opportunity to gather experience in:
- Evolutionary algorithms theory and implementation.
- How to make an experimental analysis.
- Scientific writing
- DevOps on a cluster environment.