Buch, Englisch, 300 Seiten, Format (B × H): 229 mm x 150 mm, Gewicht: 450 g
Fuzzy and Belief Degree-Based Uncertainties
Buch, Englisch, 300 Seiten, Format (B × H): 229 mm x 150 mm, Gewicht: 450 g
ISBN: 978-0-323-99444-6
Verlag: Elsevier Science
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.
Zielgruppe
<p>Graduate students, researchers, and professional engineers who study or perform optimization and evaluation; in the fields of applied mathematics, industrial engineering, computer science, information science, management science, economics, and operations research</p>
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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