Anzeige
Erschienen in:
2015 | OriginalPaper | Buchkapitel
6. Optimization of Mixed Control Supply Chain Logistics Planning Under Uncertain Environment
verfasst von : Juping Shao, Yanan Sun, Bernd Noche
Erschienen in: Optimization of Integrated Supply Chain Planning under Multiple Uncertainty
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Usually, the demand is described with random variables under uncertain environment. When we describe the demand with variables, we need a great amount of empirical statistics to get the distribution function. However, these data might be hard to get in some cases. The fussy sets theory is then a commonly used and effective method which can quantifiably describe the uncertain demand. The membership function of fuzzy numbers can be determined by the decision makers when using fuzzy numbers to describe the demand, which is much easier to determine the membership function than the determination of distribution functions of random variable.