Intelligent Fuzzy Decision Making for Industrial Production Planning
Intelligent Decision Making in an unpredictable uncertain Fuzzy Environment
Versandkostenfrei!
Versandfertig in 6-10 Tagen
39,99 €
inkl. MwSt.
PAYBACK Punkte
20 °P sammeln!
Any modern industrial manufacturing unit inevitably faces problems of vagueness in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by marketing department. This problem has to be solved by a methodology which takes care of such fuzzy information. As the analyst solves this problem, the decision maker and the implementer have to coordinate with the analyst for taking up a decision on a successful strategy for implementation. Such a complex problem of vagueness and uncertainty can be handled by the theo...
Any modern industrial manufacturing unit inevitably faces problems of vagueness in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by marketing department. This problem has to be solved by a methodology which takes care of such fuzzy information. As the analyst solves this problem, the decision maker and the implementer have to coordinate with the analyst for taking up a decision on a successful strategy for implementation. Such a complex problem of vagueness and uncertainty can be handled by the theory of fuzzy logic.In this book, a new fuzzy logic based methodology using a specific membership function, named as modified S-curve membership function is proposed. The modified S-curve membership function is first formulated and its flexibility in taking up vagueness in parameters is established by an analytical approach.The usefulness of this modified S-curve membership function is furtherestablished using a real life industrial production planning of a chocolate manufacturing unit.
Andere Kunden interessierten sich für
