HC and ILS solver

This project is an academic implementation of both HillClimbing (HC) and Iterated Local Search (ILS) for meta-heuristics learning purposes.

Both heuristics benefits from shared Meta.Problem module and it's inner types.

Benchmarks were conducted using the Meta.Functions.example_one and Meta.Functions.example_two equations and more info is provided in the Benchmarks Page.

Full Documentation

Code Implementation Details

The algorithms were implemented using the Elixir language in a Mix project environment and ex-docs documentation and an ExUnit testing framework. All code source is open-source in the github repository.

Also the API Reference displays all kind of details in modules and structs implemented, as well as the module doc tests.

Overall, the problems were implemented in a pure functional fashion using a GenServer and messages-to-self process for quick iteration and control over implementation. More details in the modules docs.

Running

A Dockerfile and docker-compose.yml files is provided in this project for quick setup and run:

docker-compose run tp1

The default entrypoint is the running of all benchmarks problems, which can then be further analysed in the benchmarks/analysis.ipynb notebook.

Full Documentation

Generating Docs

With the Docker environment, to generate a docs folder with the ExDoc files is easy as

docker-compose run tp1 mix docs --output docs

Testing

Automated test is also implemented in moduledocs test, and can be run with the command below:

docker-compose run tp1 mix test

Which will yield a result close to the one below:

root@99e6f88b669d:/code# mix test
Compiling 10 files (.ex)
Generated code app
............

Finished in 0.05 seconds (0.05s async, 0.00s sync)
12 doctests, 0 failures