Soft computing of the Borda count by fuzzy linguistic quantifiers
Borda count is a well-known social choice method frequently used for group decision making problems, however, it does not consider the optimistic/pessimistic view of the director, which has a great effect on group decisions. In the present study, the traditional Borda method is extended 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 a more intelligent procedure. Borda-OWA is then applied on two real case studies of forest management and projects ranking. The outcomes show that the Borda-OWA operator produces more soft and sensitive results by using the director's risk attitudes, guided by the fuzzy linguistic quantifiers. These results are examined by sensitivity analysis, which shows the significance of selecting the suitable quantifier. It is also shown that the original Borda is a special case of the Borda-OWA approach, indicating only the neutral view for the director. Because of the uncertainty in selecting the quantifier, we have defined 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 decision to the stakeholders whose optimism degrees are different than that of the group director. (C) 2010 Elsevier B.V. All rights reserved.
borda count fuzzy linguistic quantifiers group decision making ordered weighted averaging optimism/pessimism natural resources management