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.54(3), 269a277 (1993b) Song, K.-B., Baek, Y.-S., Hong, D.-H.: Short-term load forecasting for the holidays using fuzzy linear ... L.-Y., Cheng, C.-H.: A GA- weighted ANFIS model based on multiple stock market volatility causality for TAIEX forecasting. ... demand estimation using an adaptive neuro-fuzzy network: a case study from the Ontario provinceaCanada. Energy 49, 323a328 (2013) Zhang, Q., Liu, T.: Research on the mid-long term electric load forecasting based on fuzzy rules.
|Title||:||Supply Chain Management Under Fuzziness|
|Author||:||Cengiz Kahraman, Başar Öztayşi|
|Publisher||:||Springer - 2014-02-15|