This monograph is intended for graduate courses in engineering and management science, as well as readers who want an introduction to the theories and methologies of Multiple Attribute Decision Making (MADM) in a fuzzy environment. Classical MADM introduces a great deal of complexity to the decision analysis. In a fuzzy environment, the decision analysis is extended to consider not only the aggregation of performance scores (which are fuzzy) but also the comparison of fuzzy numbers which cannot be easily compared as in the case of real numbers. Chapter 2 gives an overview of classical MADM. Chapter 3 presents the basic concepts and the mathematical operations of fuzzy set theory with figures and simple numerical examples in an easy-to-read and easy-to-follow manner. Chapter 4 deals with fuzzy ranking methods, which are widely used in many fuzzy applications (especially fuzzy optimization procedure). A systematic classification of nearly two dozen existing ranking methods is presented, and a system for classifying over one dozen fuzzy MADM methods is presented.
The concept, algorithm and the characteristics of each method are discussed, and the computational procedure of each method is illustrated by solving a simple numerical example.

Assisted by: F.P. Hwang