Intuitionistic Fuzzy Decision Analysis with Dissonance Reduction Foroptimistic/Pessimistic Decision Makers

Atanassov所發展之直覺模糊集合理論，已成功地應用在多準則分析的領域。然而，樂觀與悲觀在直覺模糊決策中所扮演的角色鮮少探討，特別是對伴隨決策過程中之主觀判斷與認知失調的影響。在 Atanassov直覺模糊決策環境之下，本研究提出減少認知失調與考量樂觀和悲觀之多準則決策分析方法。我們利用樂觀及悲觀運算子，分別來衡量樂觀主義與悲觀主義的影響，並進一步透過加權計分函數來構建適合度模型。考慮到二個目標：最大化適合度及認知失調降低程度，本研究建構出幾個最佳化模型，以求得評估準則之最佳權重，並獲取與適合度相對應的方案排序。我們期望此方法能有效處理決策者樂觀、悲觀特質在認知失調與決策分析的影響。
The theory of Atanassov’s intuitionistic fuzzy sets has been developed and has been successfully applied in the field of multiple criteria analysis. However, there is a lack of information about the role of optimism and pessimism on subjective judgments and cognitive dissonance accompanying the decision process. This paper presents a new method of reducing cognitive dissonance and relating optimism and pessimism to multiple criteria decision analysis under Atanassov’s intuitionistic fuzzy decision environment. We utilize optimistic and pessimistic point operators to measure the effects of optimism and pessimism, respectively, and further determine the suitability function through weighted score functions. Considering two objectives of maximal suitability and dissonance reduction, several optimization models are constructed to obtain optimal weights for criteria and to acquire the corresponding suitability degree for alternative rankings. We anticipate that the proposed method will give insight into the influences of optimism, pessimism, and cognitive dissonance on decision analysis.