A computer program for multiple-attributes multiple-atlernatives decision making problem using fuzzy sets



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This thesis presents an algorithm for a multiple-attributes multiple-alternatives decision making problem based on fuzzy set theory. The computer program which implements the algorithm will handle a large data base defining imprecise relationships between input information and possible outcomes. An application of the algorithm to the problem of ranking possible diseases using chemical laboratory test data is given here to show the capability of this program. A computer program has been designed so as to minimize the memory size and computation time. The three main components of this program are: (1) Determination of membership functions based on input data, (2) Determintaion of possible outcomes using fuzzy algorithm, and (3) Ranking of the possible outcomes. Results of testing the computer program with the medical diagnosis problem and other decision problems are given.