01415nam--2200397---450-99000308154020331620080424132152.03-540-73000-1000308154USA01000308154(ALEPH)000308154USA0100030815420080317d2007----km-y0itay50------baengDEy---||||001yyComputation and logic in the real worldThird conference on computability in Europe, CiE 2007Siena, Italy, June 18-23, 2007proceedingsS. Barry Cooper, Benedikt Lowe, Andrea Sorbi (Eds.)Berlin [etc.]Springercopyr. 2007XVIII, 826 p.24 cmLecture notes in computer science44972001Lecture notes in computer science4497Principi matematici <informatica>CongressiSiena2007004.0151COOPER,S. BarryLOWE,BenediktSORBI,AndreaConference on Computability in Europe, CiE 2007<3.;2007;Siena>600756ITAsalbcISBD990003081540203316001 LNCS 449735114/CBS00100224745BKSCIANGELA9020080317USA011003ANGELA9020080424USA011321Computation and logic in the real world1023612UNISA03331oam 2200445 450 99654683640331620231114204823.0981-9931-69-X10.1007/978-981-99-3169-9(CKB)27113548000041(MiAaPQ)EBC30603278(Au-PeEL)EBL30603278(DE-He213)978-981-99-3169-9(PPN)272273589(EXLCZ)992711354800004120230921d2023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierDeriving priorities from incomplete fuzzy reciprocal preference relations theories and methodologies /Yejun XuFirst edition.Singapore :Springer,[2023]©20231 online resource (180 pages)9789819931682 Chapter 1. Introduction -- Chapter 2. Normalizing Rank Aggregation-based Method -- Chapter 3. Eigenvector Method -- Chapter 4. Logarithmic Least Squares Method -- Chapter 5. A Chi-Square Method -- Chapter 6. A Least Deviation Method -- Chapter 7. Priorities from Fuzzy Best Worst Method Matrix -- Chapter 8. Weighted Least Square Method -- Chapter 9. Priorities from Incomplete Hesitant Fuzzy Reciprocal Preference Relations.As we know, multiplicative preference relations (or called pairwise comparisons in AHP) were proposed by Dr. Thomas L Saaty. One important work is to derive its priority from pairwise comparisons. It has been proposed many methods to derive priority for multiplicative preference relation. On the basis of fuzzy sets, the fuzzy reciprocal preference relation is proposed and is extended to the incomplete contexts. However, how to derive the priorities from incomplete fuzzy reciprocal preference relations is an interesting and challenging work. This book systematically presents the theories and methodologies for deriving priorities from incomplete fuzzy reciprocal preference relations. This book can be divided into three parts. In the first part, this book introduces the basic concepts of fuzzy reciprocal preference relations and incomplete fuzzy reciprocal preference relations. Then, two consistencies of complete fuzzy reciprocal preference relations are introduced: additive consistency and multiplicative consistency. Then, the relationships between the fuzzy reciprocal elements and the weights are showed. Afterward, in the second part, different priority methods are presented. The inconsistency repairing procedures are also proposed. Last, the priority method for incomplete hesitant fuzzy reciprocal preference relations is presented. This book can be used as a reference for researchers in the areas of management science, information science, systems engineering, operations research, and other relevant fields. It can also be employed as a textbook for upper-level undergraduate students and graduate students.Fuzzy setsFuzzy sets.511.3223Xu Yejun1368807MiAaPQMiAaPQMiAaPQBOOK996546836403316Deriving Priorities from Incomplete Fuzzy Reciprocal Preference Relations3394829UNISA