Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability

A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the

Enhanced genetic algorithm-based fuzzy multiobjective strategy to multiproduct batch plant design

The design of such plants necessary involves how equipment may be utilized, which means that plant scheduling and production must form an integral part of the design problem. This work proposes an alternative treatment of the imprecision (demands) by using fuzzy concepts. In this study, we introduce a new approach to the design problem based on a multiobjective genetic algorithm, taking into account simultaneously maximization of the net present value NPV ~ and two other performance criteria, i.e. the production delay/advance and a flexibility criterion. The methodology provides a set of scenarios that are helpful to the decision’s maker and constitutes a very promising framework for taken imprecision into account in new product development stage. Besides, a hybrid selection method Pareto rank-tournament was proposed and showed a better performance than the classical Goldberg’s wheel, systematically leading to a higher number of non-dominated solutions