Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects

Abstract

Selection problems are common in process engineering. In most cases, it is necessary to rank alternatives based on multiple criteria (e.g., cost, safety, environmental impact), which are often conflicting. In addition, some criteria may be fundamentally difficult to quantify due to data scarcity, in which case subjective assessments need to be used as a proxy. Decision analysis tools such as the analytic hierarchy process (AHP) are useful to ensure decision-making is done rationally. In this work, we propose a fuzzy AHP variant, wherein pairwise comparison of decision elements by domain experts is expressed with triangular fuzzy numbers. This approach allows the degree of confidence of the expert to be quantified explicitly; it also allows inconsistencies in judgment to be reconciled within the bounds of the fuzzy numbers to generate reasonable values for the weighting factors. We demonstrate the methodology on three case studies, involving the comparison of different types of chlor-alkali electrolytic cells, CO2 capture techniques in cement plants and wastewater treatment options for municipal wastewater.