An Introduction to Fuzzy Linear Programming Problems : Theory, Methods and Applications / by Jagdeep Kaur, Amit Kumar
By: Kaur, Jagdeep
Contributor(s): SpringerLink (Online service)
| Kumar, Amit
Material type:
E-bookSeries: (Studies in Fuzziness and Soft Computing, 1434-9922; 340).Publisher: Cham : Springer International Publishing, 2016Description: 1 recurso en línea (XV, 119 páginas) :.ISBN: 9783319312743.Subject: Inteligencia artificial
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA279.6 K387 2016 EB (Browse shelf(Opens below)) | .i11593866 | Acceso electrónico | eBOOK .i11593866 |
State of the Art -- Non-Negative Fuzzy Optimal Solution of Fully Fuzzy Linear Programming Problems with Equality Constraints -- Fuzzy Optimal Solution of Fully Fuzzy Linear Programming Problems with Equality Constraints -- Fuzzy Optimal Solution of Fully Fuzzy Linear Programming Problems With Equality Constraints Having LR Flat Fuzzy Numbers -- Unique Fuzzy Optimal Value of Fully Fuzzy Linear Programming Problems With Equality Constraints Having LR Flat Fuzzy Numbers -- Future Scope.
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
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