Fuzzy-based ant colony optimization algorithm

Real world problems don´t always come with sufficient, complete, and precise data; classical algorithms are facing some limitations like inefficiency of handling imprecise data or uncertain information. Therefore there is a need for finding powerful techniques to handle such situations. The main objective of this research is to introduce a new version of ant algorithm that can solve the problems, which contain uncertain information or imprecise data. To achieve this objective, the research integrates fuzzy logic and ant algorithm for better handling of such problems.