Movement towards more sustainable waste management practice has been identified as a priority in the whole of EU. The EU Waste Management Strategy's requirements emphasize waste prevention; recycling and reuse; and improving final disposal and monitoring. In addition, in Hungary the national waste strategy requires an increase in the household waste recycling and recovery rates. Integrated waste management system (IWMS) can be defined as the selection and application of suitable and available techniques, technologies and management programs to achieve waste management objectives and goals. In this paper, the concept of ‘key drivers’ are defined as factors that change the status quo of an existing waste management system in either positive or negative direction. Due to the complexity and uncertainty occurring in sustainable waste management systems, we propose the use of fuzzy cognitive map (FCM) and bacterial evolutionary algorithm (BEA) methods to support the planning and decision making process of integrated systems, as the combination of the FCM and BEA seem to be suitable to model complex mechanisms such as IWMS. Since the FCM is formed for a selected system by determining the concepts and their relationships, it is possible to quantitatively simulate the system considering its parameters. The goal of optimization was to find such a connection matrix for FCM that makes possible to generate the most similar time series. This way a more objective description of IWMS can be given. While the FCM model represents the IWMS as a whole, BEA is used for parameter optimization and identification. Based on the results, in the near future we intend to apply the systems of systems (SoS) approach to regional IWMS.
- Bacterial evolutionary algorithm
- Fuzzy cognitive map
- Integrated waste management system
- Sustainability factors
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Computational Mathematics