Fuzzy logic modifications of the Analytic Hierarchy Process |
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| Institution: | 1. Actuarial Science Program, Smeal College of Business, Penn State University, University Park, PA 16802, USA;2. Actuarial Science Program, Department of Mathematics, University of Wisconsin-Eau Claire, Eau Claire, WI, 54701, USA;1. Department of Obstetrics and Gynecology, University of Alberta, Edmonton, Alberta, Canada;2. Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada;3. Ray D. Wolfe Department of Family Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada;4. Population, Public, and Aboriginal Health, Alberta Health Services, Edmonton, Alberta, Canada;5. College of Nursing, Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada;6. Faculty of Nursing, University of Alberta, Edmonton, Alberta, Canada;7. Department of Obstetrics and Gynecology, Radiology, McMaster University, Hamilton, Ontario, Canada;8. Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada;9. Division of Gastroenterology, University of Alberta, Edmonton, Alberta, Canada;10. St. John of God Chair Perinatal and Women’s Mental Health, School Psychiatry, University of New South Wales, Sydney, New South Wales, Australia;1. Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS), Shandong Provincial Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai, Shandong 264003, PR China;2. University of Chinese Academy of Sciences, Beijing 100049, PR China |
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| Abstract: | The Analytic Hierarchy Process (AHP) is a measurement methodology based on pair-wise comparisons that relies on judgment to derive priority scales. During its implementation, one constructs hierarchies, then makes judgments or performs measurements on pairs of elements with respect to a criterion to derive preference scales, which are then synthesized throughout the structure to select the preferred alternative.One of the areas where the AHP finds application is in the subjective phases of risk assessment (RA), where it is used to structure and prioritize diverse risk factors, including the judgments of experts. Since fuzzy logic (FL) has been shown to be an effective tool for accommodating human experts and their communication of linguistic variables, there has been research aimed at modeling the fuzziness in the AHP (FAHP), and recently the focus of some of that modeling has been with respect to RA.The literature discusses more than one FAHP model, which raises the question as to which are the prominent models and what are their characteristics. In response to this question, we examine three of the most influential FAHP models. The article proceeds as follows. It begins with a brief overview of the AHP and its limitations when confronted with a fuzzy environment. This is followed by a discussion of FL modifications of the AHP. A RA-based likelihood score example is used throughout. The article ends with a commentary on the findings. |
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| Keywords: | Analytic Hierarchy Process Fuzzy logic Fuzzy analytic hierarchy process Risk assessment Likelihood |
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