About this book

• The first book comprehensively introduces uncertain DEA
• A comprehensive coverage of models, sensitivity, ranking criteria and congestion in uncertain DEA
• The book is classified by measures rather than models
  

This book is intended to present the milestones in the progression of uncertain Data envelopment analysis (DEA). Chapter 1 gives some basic introduction to uncertain theories, including probability theory, credibility theory, uncertainty theory and chance theory. Chapter 2 presents a comprehensive review and discussion of basic DEA models. The stochastic DEA is introduced in Chapter 3, in which the inputs and outputs are assumed to be random variables. To obtain the probability distribution of a random variable, a lot of samples are needed to apply the statistics inference approach. Chapter 4 and 5 provide two uncertain DEA methods to evaluate the DMUs with limited or insufficient statistical data, named fuzzy DEA and uncertain DEA. In order to evaluate the DMUs in which uncertainty and randomness appear simultaneously, the hybrid DEA based on chance theory is presented in Chapter 6.


Content Level » Research

Keywords » Congestion analysis - Credibility variable - Data envelopment analysis - Fuzzy DEA - Fuzzy simulation - Genetic algorithm - Hybrid DEA - Random variable - Ranking criteria - Sensitivity and stability - Stochastic DEA - Uncertain DEA - Uncertain random variable

Related subjects » Operations Research & Decision Theory