The NovEDAR_EDSS was conceived as an integrated software employing artificial intelligence techniques combined with different analytical tools: Multicriteria Decision Analysis (MCDA) methodologies [20], LCA, Cost-Benefit Analysis (CBA) and Environmental-Benefit Analysis (EBA)[21]. The NovEDAR_EDSS has previously been successfully used in feasible WWTP selections [22] including economic parameter evaluation [21]. The proposed EDSS model was based on a hierarchical decision approach combined with a knowledge-based system, which uses the interaction of different main knowledge bases to provide a required number of optimum alternatives. The aim of this study was to assess the selection between five alternatives for sludge treatment, embracing economic and GWP issues. In doing so, five scenarios regarding the stakeholders' preferences are evaluated using a WWTP with a one million person equivalent (PE) capacity as a case study. The most relevant factors contributing to the overall plant feasibility and GWP of the evaluated alternatives was identified and …show more content…
The study of large WWTPs enables exploration of a wide variety of alternatives in the design of sludge treatment. The output information of the EDSS shows technically feasible sludge process flow diagrams. In this study, five representatives and different configuration alternatives among the set of technically suitable options were selected according to the three main criteria implemented in the EDSS: economy, environmental and technical. The NovEDAR_EDSS suggests a WWTP process flow diagram based on the case study data In addition, it provides a complete set of estimated output data from the corresponding groups of technologies within sludge line-related sections. The proposed approach contributes to the implementation of more suitable sewage sludge treatment lines since it provides an indicator for each alternative embracing economic and GWP issues.
2.4. REVIEWED METHODOLOGY FOR DESIGN AND DEVELOPMENT OF DSS
An organization of any size deals with numerous pieces of information. [23]. The Decision Support System (DSS) may be developed using following ways:
• Prototype method: In the prototype method, initial methods are developed first. Once implemented, the system is refined and modified as per new specifications. This iterative process is followed till the user accepts the system
• Life cycle approach: In life cycle approach, the DSS development