Evaluation methodologies for technology selection

This paper presents a technology selection algorithm to quantify both tangi ble and intangible benefits in fuzzy environment. Specifically, it describe s an application of the theory of fuzzy sets to hierarchical structural ana lysis and economic evaluations. From the analytical point of view, decision -makers are asked to express their opinions on comparative importance of va rious factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as "very high", "high", "medium", "low" a nd "very low", are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than i n an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate ind ex. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the econom ic evaluation perspective, a fuzzy cash flow analysis is employed. Since co nventional engineering economic analysis involves uncertainty about future cash flows where cash flows are defined as either crisp numbers or risky pr obability distributions, the results of analysis may obscure. To deal quant itatively with imprecision or uncertainty, cash flows are modeled as triang ular fuzzy numbers which represent "the most Likely possible value", "the m ost pessimistic value" and "the most optimistic value". By using this algor ithm, the ambiguities involved in the assessment data can be effectively re presented and processed to assure a more convincing and effective decision- making. (C) 2000 Elsevier Science B.V. All rights reserved.