Classical data envelopment analysis (DEA) models use crisp data to measure the inputs and outputs of a given system. In cases such as manufacturing systems, production processes, service systems, etc., the inputs and outputs may be complex and difficult to measure with classical DEA models. Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex uncertain data, then they will become more important and practical for decision makers. Uncertainty in Data Envelopment Analysis introduces methods to investigate uncertain data in DEA…mehr
Classical data envelopment analysis (DEA) models use crisp data to measure the inputs and outputs of a given system. In cases such as manufacturing systems, production processes, service systems, etc., the inputs and outputs may be complex and difficult to measure with classical DEA models. Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex uncertain data, then they will become more important and practical for decision makers. Uncertainty in Data Envelopment Analysis introduces methods to investigate uncertain data in DEA models, providing a deeper look into two types of uncertain DEA methods, fuzzy DEA and belief degree-based uncertainty DEA, which are based on uncertain measures. These models aim to solve problems encountered by classical data analysis in cases where the inputs and outputs of systems and processes are volatile and complex, making measurement difficult.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
Produktdetails
Uncertainty, Computational Techniques, and Decision Intelligence
Dr. Lotfi is a Full Professor of Mathematics at the Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran. In 1992, he received his undergraduate degree in Mathematics at Yazd University, Yazd, Iran. He received his M.Sc in Operations Research at IAU, Lahijan, Iran in 1996 and PhD in Applied Mathematics (O.R.) at IAU, Science and Research Branch, Tehran, Iran in 2000. His major research interests are operations research and data envelopment analysis. He has published more than 300 scientific and technical papers in leading scientific journals, including European Journal of Operational Research, Computers and Industrial Engineering, Journal of the Operational Research Society, Applied Mathematics and Computation, Applied Mathematical Modelling, Mathematical and Computer Modelling, and Journal of the Operational Research Society of Japan, etc. He is Editor-in-Chief and member of editorial board of Journal of Data Envelopment Analysis and Decision Science. He is also Director-in-Charge and member of editorial board of International Journal of Industrial Mathematics.
Inhaltsangabe
1. Uncertain Theories 2. Introduction to Data Envelopment Analysis 3. Fuzzy Data Envelopment Analysis 4. Ranking and Sensitivity and Stability in Fuzzy DEA 5. Uncertain Data Envelopment Analysis 6. Ranking and Sensitivity and Stability in Uncertain DEA
1. Uncertain Theories 2. Introduction to Data Envelopment Analysis 3. Fuzzy Data Envelopment Analysis 4. Ranking and Sensitivity and Stability in Fuzzy DEA 5. Uncertain Data Envelopment Analysis 6. Ranking and Sensitivity and Stability in Uncertain DEA
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