Soft Computing of the Borda Count by Fuzzy Linguistic Quantifiers

Borda count is a well-known social choice method, and is frequently used for group decision making problems. However it does not consider the optimism/pessimism view of the director, which has a great effect on the group decisions. Therefore in the present study, we extend the Borda method by using the Ordered Weighted Averaging (OWA) operator to consider the risk attitudinal characteristics. The new approach, entitled Borda-OWA, solves the group decision making problem in an intelligent procedure. It is then applied on two real case studies of forest management and projects ranking. The outcomes show that the Borda-OWA operator makes more soft and sensitive results by using the director’s risk attitudes, guided by the fuzzy linguistic quantifiers. The new results are also examined by sensitivity analysis, which shows the importance of selecting the suitable quantifier. It is shown that the original Borda is a special case of the Borda-OWA approach, indicating only the neutral view of the director. Because of the uncertainty in selecting the quantifier, we define a new measure which considers both the expected value and the variance of the combined goodness measure for each alternative. By using this measure the Borda-OWA model will give more robust decisions to the stakeholders whose optimism degrees are different than that of the group director.