ranking with fuzzy data with The secondary goal in order to adding optimal prefix to the feasible area of the CCR Multiplier

Data envelopment analysis(DEA) models are now widely utilized in various applications for ranking processes. When CCR Model in input orientation with fuzzy data is used for ranking processes by the use of cross- efficiency the alternative optimal solution may be found. As a result, cross- efficiency tables should be achieved. In this case ,the ranking order is notunique, e.g. a Decision Making Unit(dmu) may be included several ranks. In order to resolve this problem, a secondary goal should be determined for selecting the optimal weight so according to this secondary goal a goal weight is selected among alternative optimal solutions. By this study, the secondary goal will be achieved by adding optimal prefix to each DMU (DMUK, k=1,…,n) ; also adding it to the feasible area of CCR multiplier model in an input orientation which has been used to efficiency evaluate the decision-making units with fuzzy inputs and outputs; then,the efficiencyscore of each decision-making units (DMp p=1,....n ) could be obtained in terms of the optimum weights of the other decision-making units (DMUk k=1,....n ); as a result, cross- efficiency table for the fuzzy secondary goal could be created and then ranking process done by ranking fuzzy functions. In addition to measure the efficiency of each unit in relation to the other units in this table, the decision-making units are ranked in general.

Keywords:

Data Envelopment Analysis(DEA ) Fuzzy –Data Enevlopment Analysis(F-DEA) , Ranking , Fuzzy ranking approach