Decision-making proposition of fuzzy information measure with collective restrictions

Abstract

Information theory was founded by Shannon (A mathematical theory of communication. Bell Syst Tech J 379–423, 623–659 (1948) [11]) who introduced the concept of entropy in communication theory. Information theory is concerned with communication systems and has applications in statistics, information processing, and computing. The theory of fuzzy sets which was introduced by Zadeh (Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst 3–28 (1978) [13]) gave fuzzy entropy a measure of fuzzy information which was dependent on Shannon’s entropy. A large amount of work is being done on characterization of various fuzzy entropies. In this paper, a generalized measure of fuzzy information with multiple parameters has been proposed and applications of fuzzy information measure in decision-making have been discussed.