Advanced learning of fuzzy cognitive maps of waste management by bacterial algorithm

Fuzzy cognitive maps (FCMs) are a very convenient and simple tool for modeling complex systems. They are popular due to their simplicity and user friendliness. However, according to [1], human experts are subjective and can handle only relatively simple networks therefore there is an urgent need to develop methods for automated generation of FCM models. The present research deals with the methodology of FCMs in combination with the Bacterial Evolutionary Algorithm (BEA). The method of FCMs using BEA seems to be suitable to model such complex mechanisms as integrated municipal waste management (IMWM) systems. This paper is an attempt to assess the sustainability of the IMWM system by investigating the FCM methodology based on the BEA with a holistic approach. As a result, the best scenario to an IMWM system can be assigned.