| Summary: | 碩士 === 長庚大學 === 企業管理研究所 === 97 === The ELECTRE is one of the important methods in multiple criteria decision making and can be applied to various fields. The ELECTRE belongs to an outranking method which helps us to find out the best alternative or rank the alternatives from the best to the worst. However, the manager usually makes decisions with oneself subjective aspect：optimism and pessimism, and therefore affecting the decision-making process. Beside, general ELECTRE methods often exercise crisp value to determine the preference between two alternatives, but in real world the data we obtain always are inaccurate, uncertain and vague. Hence, we use the intuitionistic fuzzy set (IFS) theory to take into account the uncertainty and vagueness which are usually inherent in data, and discuss how to transfer the IFS to ELECTRE. In brief, we incorporate the IFS and optimism/pessimism due to ambiguity to achieve a flexible decision approach suitable for uncertain and fuzzy environments.
In this study, we propose optimistic and pessimistic point operators to adjust the original matrix, and then develop two new methods which transfer the data into ELECTRE. First method named ES obtains optimistic and pessimistic score functions, the second method named EI combined the accuracy function and inequality relations to develop and define three concordance sets and three discordance sets. Finally, associating the TOPSIS method to revises the ELECTRE’s problems which have to build threshold and probably obtain only partial order, we find a new way to obtain the totally order.
The feasibility and practicability of the proposed method were examined by an empirical study. The stimuli of the empirical study are bank service and amusement park. The LOT with unidimensional measure is used to determine dispositional optimism and pessimistic. The empirical results indicate that compared with the methods without any operators to adjust, the methods using optimistic and pessimistic point operators can generate the ranks which more correspond to the decision makers’ thoughts.
|
|---|
