Solving industrial decision making problems using fuzzy numbers

Human-based industrial decision making normally involves both quantitative and qualitative input factors. Subjectiveness in human evaluation is unavoidable in the decision making process. In fuzzy-based industrial decision making environment where fuzzy numbers are used to evaluate subjective factors, ranking of fuzzy numbers become one of the crucial component which need to be performed before the final decision can be reached. In this paper, a similarity-based method of ranking fuzzy numbers is proposed. The applicability of the proposed method in solving selected industrial-related decision making problems namely the risk evaluation and pattern recognition problems are illustrated.