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Fuzzy linear programmingsolution tec...

Cao, Bing-Yuan.

Fuzzy linear programmingsolution techniques and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fuzzy linear programmingby Seyed Hadi Nasseri, Ali Ebrahimnejad, Bing-Yuan Cao.
Reminder of title:	solution techniques and applications /
Author:	Nasseri, Seyed Hadi.
other author:	Ebrahimnejad, Ali.
Published:	Cham :Springer International Publishing :2019.
Description:	xviii, 232 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Fuzzy sets.
Online resource:	https://doi.org/10.1007/978-3-030-17421-7
ISBN:	9783030174217$q(electronic bk.)

Fuzzy linear programmingsolution techniques and applications /
Nasseri, Seyed Hadi.

Fuzzy linear programmingsolution techniques and applications /[electronic resource] :by Seyed Hadi Nasseri, Ali Ebrahimnejad, Bing-Yuan Cao. - Cham :Springer International Publishing :2019. - xviii, 232 p. :ill., digital ;24 cm. - Studies in fuzziness and soft computing,v.3791434-9922 ;. - Studies in fuzziness and soft computing ;v.273..

Preliminaries and Backgrounds -- Fuzzy Linear Programming -- Fuzzy Number Linear Programming -- Linear Programming with Fuzzy Variables -- Semi-Fully Fuzzy Linear Programming -- Application for the Flexible Linear Programming.

This book presents the necessary and essential backgrounds of fuzzy set theory and linear programming, particularly a broad range of common Fuzzy Linear Programming (FLP) models and related, convenient solution techniques. These models and methods belong to three common classes of fuzzy linear programming, namely: (i) FLP problems in which all coefficients are fuzzy numbers, (ii) FLP problems in which the right-hand-side vectors and the decision variables are fuzzy numbers, and (iii) FLP problems in which the cost coefficients, the right-hand-side vectors and the decision variables are fuzzy numbers. The book essentially generalizes the well-known solution algorithms used in linear programming to the fuzzy environment. Accordingly, it can be used not only as a textbook, teaching material or reference book for undergraduate and graduate students in courses on applied mathematics, computer science, management science, industrial engineering, artificial intelligence, fuzzy information processes, and operations research, but can also serve as a reference book for researchers in these fields, especially those engaged in optimization and soft computing. For textbook purposes, it also includes simple and illustrative examples to help readers who are new to the field.

ISBN: 9783030174217$q(electronic bk.)

Standard No.: 10.1007/978-3-030-17421-7doiSubjects--Topical Terms:

182529
Fuzzy sets.

LC Class. No.: QA248.5 / .N377 2019

Dewey Class. No.: 511.3223

Fuzzy linear programmingsolution techniques and applications /
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245 1 0 $a Fuzzy linear programming $h [electronic resource] : $b solution techniques and applications / $c by Seyed Hadi Nasseri, Ali Ebrahimnejad, Bing-Yuan Cao.
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505 0 $a Preliminaries and Backgrounds -- Fuzzy Linear Programming -- Fuzzy Number Linear Programming -- Linear Programming with Fuzzy Variables -- Semi-Fully Fuzzy Linear Programming -- Application for the Flexible Linear Programming.
520 $a This book presents the necessary and essential backgrounds of fuzzy set theory and linear programming, particularly a broad range of common Fuzzy Linear Programming (FLP) models and related, convenient solution techniques. These models and methods belong to three common classes of fuzzy linear programming, namely: (i) FLP problems in which all coefficients are fuzzy numbers, (ii) FLP problems in which the right-hand-side vectors and the decision variables are fuzzy numbers, and (iii) FLP problems in which the cost coefficients, the right-hand-side vectors and the decision variables are fuzzy numbers. The book essentially generalizes the well-known solution algorithms used in linear programming to the fuzzy environment. Accordingly, it can be used not only as a textbook, teaching material or reference book for undergraduate and graduate students in courses on applied mathematics, computer science, management science, industrial engineering, artificial intelligence, fuzzy information processes, and operations research, but can also serve as a reference book for researchers in these fields, especially those engaged in optimization and soft computing. For textbook purposes, it also includes simple and illustrative examples to help readers who are new to the field.
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