By Witold Pedrycz
Fuzzy Multicriteria Decision-Making: versions, Algorithms and Applications addresses theoretical and functional gaps in contemplating uncertainty and multicriteria elements encountered within the layout, making plans, and keep an eye on of complicated platforms. together with all prerequisite wisdom and augmenting a few elements with a step by step rationalization of extra complicated techniques, the authors offer a scientific and finished presentation of the suggestions, layout method, and distinct algorithms. those are supported by means of many numeric illustrations and a few program situations to encourage the reader and make a few summary innovations extra tangible.
Fuzzy Multicriteria Decision-Making: versions, Algorithms and Applications will attract a large viewers of researchers and practitioners in disciplines the place decision-making is paramount, together with numerous branches of engineering, operations examine, economics and administration; it's going to even be of curiosity to graduate scholars and senior undergraduate scholars in classes akin to determination making, administration, chance administration, operations learn, numerical tools, and knowledge-based systems.Content:
Chapter 1 Decision?Making in process venture, making plans, Operation, and keep an eye on: Motivation, targets, and simple innovations (pages 1–19):
Chapter 2 Notions and ideas of Fuzzy units: An creation (pages 21–62):
Chapter three chosen layout and Processing elements of Fuzzy units (pages 63–102):
Chapter four non-stop types of Multicriteria Decision?Making and their research (pages 103–136):
Chapter five creation to choice Modeling with Binary Fuzzy family (pages 137–153):
Chapter 6 development of Fuzzy choice kinfolk (pages 155–191):
Chapter 7 Discrete versions of Multicriteria Decision?Making and their research (pages 193–246):
Chapter eight Generalization of a vintage method of facing Uncertainty of knowledge for Multicriteria determination difficulties (pages 247–261):
Chapter nine team Decision?Making: Fuzzy versions (pages 263–291):
Chapter 10 Use of Consensus Schemes in staff Decision?Making (pages 293–333):
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Extra info for Fuzzy Multicriteria Decision-Making: Models, Methods and Applications
Given the enormous diversity of potentially useful (namely, semantically sound) membership functions, there are certain common characteristics (descriptors) that are conceptually and operationally qualified to capture the essence of the granular constructs represented in terms of fuzzy sets. In what follows, we provide a list of the descriptors commonly encountered in practice. 10) x∈X If this property does not hold, we call the fuzzy set subnormal. 7. The supremum (sup) in the above expression is also referred to as the height of the fuzzy set A, hgt(A) = sup A(x) = 1.
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