Fuzzy pair-wise dominance and fuzzy indices: An evaluation of productive performance |
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| Institution: | 1. System Performance Laboratory, Department of Industrial and Systems Engineering, Virginia Tech/Northern Virginia Center, 7054 Haycock Road, Falls Church, VA 22043-2311, USA;2. Department of Economics, Louisiana State University, Baton Rouge, LA 70803, USA;3. Institute of Industrial Engineering and Management, Wroclaw University of Technology, ul. Smoluchowskiego 25, 50-370 Wroclaw, Poland;1. Department of Ophthalmology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan;2. Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan;1. School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100191, PR China;2. School of Accounting and Finance, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;3. School of Business Administration, China University of Petroleum, Beijing 102249, PR China;1. School of Medicine, Henan University, Kaifeng, China;2. School of College English Teaching and Research, Henan University, Kaifeng, China;1. Wright State University, Department of Leadership Studies in Education and Organizations, 3640 Colonel Glenn Highway, Dayton, OH, 45435, USA;2. Wright State University, Department of Computer Science and Engineering, 3640 Colonel Glenn Highway, Dayton, OH, 45435, USA;3. Wright State University, Department of Biological Sciences, 3640 Colonel Glenn Highway, Dayton, OH 45435, USA;4. Arizona State University, Human Systems Engineering, 7271 E. Sonoran Arroyo Mall, Mesa, AZ, 85212, USA |
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| Abstract: | Usually, efficiency measurement and evaluation are based on the definition of a frontier that envelops the observed production plans. Measurement and evaluation of productive performance is also achieved with the concept of pair-wise dominance that does not require the existence of a frontier along with the required technological assumptions needed for its definition. In situations where measurement inaccuracies occur, the traditional assumption of crisp production plans can be substituted with the alternative assumption of fuzzy production plans as proposed by fuzzy set theory. This research presents indices that capture the degree to which pair-wise dominance occurs between two fuzzy production plans. The proposed approach is based on the various comparison indices known from the literature that are used to compare fuzzy intervals and is compared with an earlier fuzzy pair-wise classification scheme. Finally, the approach is used to evaluate the productive performance of suspect production plans from the preprint insertion manufacturing process. |
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