Multiple Criteria Decision Making Methods with Multi-polar Fuzzy Information Algorithms and Applications /
Akram, Muhammad.
Multiple Criteria Decision Making Methods with Multi-polar Fuzzy Information Algorithms and Applications / [electronic resource] : by Muhammad Akram, Arooj Adeel. - 1st ed. 2023. - XXXIV, 540 p. 74 illus., 35 illus. in color. online resource. - Studies in Fuzziness and Soft Computing, 430 1860-0808 ; . - Studies in Fuzziness and Soft Computing, 430 .
Acceso multiusuario
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.
9783031436369
Computational intelligence.
Operations research.
Computational Intelligence.
Operations Research and Decision Theory.
Q342
006.3
Multiple Criteria Decision Making Methods with Multi-polar Fuzzy Information Algorithms and Applications / [electronic resource] : by Muhammad Akram, Arooj Adeel. - 1st ed. 2023. - XXXIV, 540 p. 74 illus., 35 illus. in color. online resource. - Studies in Fuzziness and Soft Computing, 430 1860-0808 ; . - Studies in Fuzziness and Soft Computing, 430 .
Acceso multiusuario
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.
9783031436369
Computational intelligence.
Operations research.
Computational Intelligence.
Operations Research and Decision Theory.
Q342
006.3
