Buch, Englisch, 275 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 606 g
Buch, Englisch, 275 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 606 g
Reihe: Uncertainty and Operations Research
ISBN: 978-981-10-3264-6
Verlag: Springer Nature Singapore
This book offers a comprehensive and systematic introduction to the latest research on hesitant fuzzy decision-making theory. It includes six parts: the hesitant fuzzy set and its extensions, novel hesitant fuzzy measures, hesitant fuzzy hybrid weighted aggregation operators, hesitant fuzzy multiple-criteria decision-making with incomplete weights, hesitant fuzzy multiple criteria decision-making with complete weights information, and the hesitant fuzzy preference relation based decision-making theory. These methodologies are implemented in various fields such as decision-making, medical diagnosis, cluster analysis, service quality management, e-learning management and environmental management. A valuable resource for engineers, technicians, and researchers in the fields of fuzzy mathematics, operations research, information science, management science and engineering, it can also be used as a textbook for postgraduate and senior undergraduate students.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Betriebssysteme
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Entscheidungstheorie, Sozialwahltheorie
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Fuzzy-Set-Theorie
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
Weitere Infos & Material
Preface.- 1 Hesitant Fuzzy Set and Its Extensions.- 2 Novel Correlation and Entropy Measures for Hesitant Fuzzy Set.- 3 Multiple Criteria Decision Making with Hesitant Fuzzy Hybrid Weighted Aggregation Operators.- 4 Hesitant Fuzzy Multiple Criteria Decision Making with Complete Weight Information.- 5 Hesitant Fuzzy Multiple Criteria Decision Making with Incomplete Weights.- 6 Decision Making with Hesitant Fuzzy Preference Relation.