Credibility-based fuzziness and incomplete information value in fuzzy programming

The research shows that traditional possibility measure has defects in dealing with fuzzy programming, while the credibility measure with self-duality is more proved better. Based on the credibility theory, many researchers study the information value and fuzziness under complete information. However, most of the real-life decision-making problems have incomplete information, and the above research methods cannot solve the problem in this situation. Therefore, based on credibility theory, we investigate the incomplete information value and fuzziness when the fuzzy information is incomplete in the fuzzy programming by employing the two-stage method. To measure the maximum size of paying for incomplete information and the importance of fuzziness, we present two optimal indices which are the expected value of incomplete information and the value of fuzzy solution, and study their theoretical properties and rationality by some numerical examples. The theoretical results obtained in this paper. The results obtained in this paper theoretically guarantees the effectiveness of fuzzy decision making on the incomplete information value in fuzzy systems.