This collection of Python3 modules provides a large range of implemented decision aiding algorithms useful in the field of outranking digraphs based Multiple Criteria Decision Aid (MCDA), especially best choice, linear ranking and absolute or relative rating algorithms with multiple incommensurable criteria. Technical documentation and tutorials are available under the following link:
https://digraph3.readthedocs.io/en/latest/
The tutorials introduce the main objects like digraphs, outranking digraphs and performance tableaux. There is also a tutorial provided on undirected graphs. Some tutorials are problem oriented and show how to compute the winner of an election, how to build a best choice recommendation, or how to
linearly rank or rate with multiple incommensurable performance criteria. Other tutorials concern more specifically operational aspects of computing maximal independent sets (MISs) and kernels in graphs and digraphs.
Features
- Algorithmic Decision Theory
- Bipolar outranking digraphs
- Selection, ranking and rating algorithms
- Multiple incommensurable criteria decision aid
- Computational epistemic {-1,0,1}-valued logic
Project Samples
