Induced Pure Linguistic OWA Operator and Its Application
首发时间:2007-01-22
Abstract:With respect to multiple attribute group decision making (MAGDM) problems, in which all the attribute weights, attribute values and the expert weights take the form of linguistic variables, by utilizing some operational laws of linguistic variables, we propose a new aggregation operator called induced pure linguistic ordered weighted averaging (IPLOWA) operator which can be utilized to aggregate preference information taking the form of pure linguistic variables, and then study some desirable properties of the IPLOWA operator. The IPLOWA operator is a more general type of aggregation operator, which is based on the pure linguistic weighted arithmetic averaging (PLWAA) and pure linguistic ordered weighted averaging (PLOWA) operators. Moreover, based on the PLWAA and IPLOWA operators, we proposed a practical method for MAGDM under pure linguistic environment. The method is straightforward and has no loss of information. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
keywords: Multiple attribute group decision making Linguistic variables Some operational laws Induced pure linguistic ordered weighted averaging (IPLOWA) operator
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Induced Pure Linguistic OWA Operator and Its Application
摘要:With respect to multiple attribute group decision making (MAGDM) problems, in which all the attribute weights, attribute values and the expert weights take the form of linguistic variables, by utilizing some operational laws of linguistic variables, we propose a new aggregation operator called induced pure linguistic ordered weighted averaging (IPLOWA) operator which can be utilized to aggregate preference information taking the form of pure linguistic variables, and then study some desirable properties of the IPLOWA operator. The IPLOWA operator is a more general type of aggregation operator, which is based on the pure linguistic weighted arithmetic averaging (PLWAA) and pure linguistic ordered weighted averaging (PLOWA) operators. Moreover, based on the PLWAA and IPLOWA operators, we proposed a practical method for MAGDM under pure linguistic environment. The method is straightforward and has no loss of information. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
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