The fuzzy mathematics of finance
Fuzzy Sets and Systems
Ranking fuzzy numbers with integral value
Fuzzy Sets and Systems
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy Sets and Systems
Fuzzy Mathematical Models in Engineering and Management Science
Fuzzy Mathematical Models in Engineering and Management Science
Capital budgeting techniques using discounted fuzzy versus probabilistic cash flows
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent information systems and applications
Prioritization of human capital measurement indicators using fuzzy AHP
Expert Systems with Applications: An International Journal
Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management
Information Sciences: an International Journal
Weapon selection using the AHP and TOPSIS methods under fuzzy environment
Expert Systems with Applications: An International Journal
Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
Combined MCDM techniques for exploring company value based on Modigliani-Miller theorem
Expert Systems with Applications: An International Journal
Evaluation model of business intelligence for enterprise systems using fuzzy TOPSIS
Expert Systems with Applications: An International Journal
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There exist a number of methods proposed in the literature to quantify manufacturing flexibility in monetary terms and to use a financial evaluation model with a decision criterion based on present worth. However, most of these methods are unable to handle problems with incomplete and uncertain data. To obtain a sensible result in quantifying the manufacturing flexibility in computer integrated manufacturing systems, this paper proposes some fuzzy models based on fuzzy present worth. The fuzzy models based on present worth are basically engineering economics decision models in which the uncertain cash flows and discount rates are specified as triangular fuzzy numbers. To build such a model, fuzzy present worth formulas of the manufacturing flexibility elements are formed, Flexibility for continuous improvement, flexibility for trouble control, flexibility for work force control, and flexibility for work-in-process control are quantified by using fuzzy present worth analysis. Formulas for both inflationary and non-inflationary conditions are derived. Using these formulas, more reliable results can be obtained especially for such a concept like flexibility that is described in many intangible dimensions. These models allow experts' linguistic predicates about computer integrated manufacturing systems.