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Multiple criteria decision making methods with multi-polar fuzzy informationalgorithms and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multiple criteria decision making methods with multi-polar fuzzy informationby Muhammad Akram, Arooj Adeel.
Reminder of title:	algorithms and applications /
Author:	Akram, Muhammad.
other author:	Adeel, Arooj.
Published:	Cham :Springer Nature Switzerland :2023.
Description:	xxxiv, 540 p. :illustrations (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Fuzzy sets.
Online resource:	https://doi.org/10.1007/978-3-031-43636-9
ISBN:	9783031436369$q(electronic bk.)

Multiple criteria decision making methods with multi-polar fuzzy informationalgorithms and applications /
Akram, Muhammad.

Multiple criteria decision making methods with multi-polar fuzzy informationalgorithms and applications /[electronic resource] :by Muhammad Akram, Arooj Adeel. - Cham :Springer Nature Switzerland :2023. - xxxiv, 540 p. :illustrations (some col.), digital ;24 cm. - Studies in fuzziness and soft computing,v. 4301860-0808 ;. - Studies in fuzziness and soft computing ;v.273..

1. Hybrid Multi-polar Fuzzy Models -- 2. TOPSIS and ELECTRE-I Methods under Multi-polar Fuzzy Linguistic Sets -- 3. Introducing Hesitancy: TOPSIS and ELECTRE-I Models -- 4. Extended ELECTRE I, II Methods with Multi-polar Fuzzy Sets -- 5. Enhanced ELECTRE III Method with Multi-polar Fuzzy Sets.

This book presents an extension of fuzzy set theory allowing for multi-polar information, discussing its impact on the theoretical and practical development of multi-criteria decision making. It reports on set of hybrid models developed by the authors, and show how they can be adapted, case by case, to the lack of certainty under a variety of criteria. Among them, hybrid models combining m-polar fuzzy sets with rough, soft and 2-tuple linguistic sets, and m-polar hesitant fuzzy sets and hesitant m-polar fuzzy are presented, together with some significant applications. In turn, outranking decision-making techniques such as m-polar fuzzy ELECTRE I, II, III and IV methods, as well as m-polar fuzzy PROMETHEE I and II methods, are developed. The efficiency of these decision-making procedures, as well as other possible extensions studied by the authors, is shown in some real-world applications. Overall, this book offers a guide on methodologies to deal with the multi-polarity and fuzziness of the real-world problems, simultaneously. By including algorithms and computer programming codes, it provides a practice-oriented reference guide to both researchers and professionals working at the interface between computational intelligence and decision making.

ISBN: 9783031436369$q(electronic bk.)

Standard No.: 10.1007/978-3-031-43636-9doiSubjects--Topical Terms:

182529
Fuzzy sets.

LC Class. No.: QA248.5

Dewey Class. No.: 511.3223

Multiple criteria decision making methods with multi-polar fuzzy informationalgorithms and applications /
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505 0 $a 1. Hybrid Multi-polar Fuzzy Models -- 2. TOPSIS and ELECTRE-I Methods under Multi-polar Fuzzy Linguistic Sets -- 3. Introducing Hesitancy: TOPSIS and ELECTRE-I Models -- 4. Extended ELECTRE I, II Methods with Multi-polar Fuzzy Sets -- 5. Enhanced ELECTRE III Method with Multi-polar Fuzzy Sets.
520 $a This book presents an extension of fuzzy set theory allowing for multi-polar information, discussing its impact on the theoretical and practical development of multi-criteria decision making. It reports on set of hybrid models developed by the authors, and show how they can be adapted, case by case, to the lack of certainty under a variety of criteria. Among them, hybrid models combining m-polar fuzzy sets with rough, soft and 2-tuple linguistic sets, and m-polar hesitant fuzzy sets and hesitant m-polar fuzzy are presented, together with some significant applications. In turn, outranking decision-making techniques such as m-polar fuzzy ELECTRE I, II, III and IV methods, as well as m-polar fuzzy PROMETHEE I and II methods, are developed. The efficiency of these decision-making procedures, as well as other possible extensions studied by the authors, is shown in some real-world applications. Overall, this book offers a guide on methodologies to deal with the multi-polarity and fuzziness of the real-world problems, simultaneously. By including algorithms and computer programming codes, it provides a practice-oriented reference guide to both researchers and professionals working at the interface between computational intelligence and decision making.
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