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Supply Chain Management Under Fuzziness [electronic resource] : Recent Developments and Techniques / edited by Cengiz Kahraman, Başar �Oztayşi.

Contributor(s): Kahraman, Cengiz [editor.] | �Oztayşi, Başar [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Fuzziness and Soft Computing: 313Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: XII, 679 p. 110 illus., 12 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642539398.Subject(s): Engineering | Production management | Computational intelligence | Engineering economics | Engineering economy | Engineering | Computational Intelligence | Engineering Economics, Organization, Logistics, Marketing | Operations ManagementAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online In: Springer eBooksSummary: Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.
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Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.

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