PC-ACO

Pairwise Comparisons-based Ant Colony Optimization

• Algorithm for solving multiple objective continuous optimization problems which allows taking into account user preferences in the form of pairwise comparisons.
• Based on the ant colony metaheuristic.
• The optimization is steered with user preferences towards more desired solutions.
• The preferences are expressed by pairwise comparisons which are translated into a value function preference model.
• 5 value function approaches are implemented and compared.
• The performance of the algorithm is tested on a set of benchmark problems.

Requirements

Available in requirements.txt. Install all required packages by running:

pip install -r requirements.txt

Running guide

Run with default parameters:

python pcaco.py

Show help about available parameters:

python pcaco.py -h

Run tests:

python -m unittest discover -s test/

Plot of an example run for WFG1