## Fuzzy Preference Modelling and Multicriteria Decision Support

Author: J.C. Fodor
Publisher: Springer Science & Business Media
ISBN: 940171648X
Format: PDF, ePub

## Fuzzy Multicriteria Decision Making

Author: Witold Pedrycz
Publisher: John Wiley & Sons
ISBN: 1119957389
Format: PDF, Mobi

Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications addresses theoretical and practical gaps in considering uncertainty and multicriteria factors encountered in the design, planning, and control of complex systems. Including all prerequisite knowledge and augmenting some parts with a step-by-step explanation of more advanced concepts, the authors provide a systematic and comprehensive presentation of the concepts, design methodology, and detailed algorithms. These are supported by many numeric illustrations and a number of application scenarios to motivate the reader and make some abstract concepts more tangible. Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications will appeal to a wide audience of researchers and practitioners in disciplines where decision-making is paramount, including various branches of engineering, operations research, economics and management; it will also be of interest to graduate students and senior undergraduate students in courses such as decision making, management, risk management, operations research, numerical methods, and knowledge-based systems.

## Preference Modelling

Author: Marc Roubens
Publisher: Springer Science & Business Media
ISBN: 3642465501
Format: PDF, Kindle

The following scheme summarizes the different families introduced in this chapter and the connections between them. Family of interval orders f Row-homogeneous Column-homogeneous Family of family of interval semi orders family of interval orders orders Homogeneous family of i nterva 1 orders Homogeneous family of semi orders Family of weak orders 85 5.13. EXAMPLES We let to the reader the verification of the following assertions. Example 1 is a family of interval orders which is neither row-homogeneous nor column-homogeneous. Example 2 is a column-homogeneous family of interval orders which is not row-homogeneous but where each interval order is a semiorder. Example 3 is an homogeneous family of interval orders which are not semiorders. Example 4 is an homogeneous family of semi orders . . 8 ~ __ --,b ~---i>---_ C a .2 d c Example Example 2 .8 .6 c .5 a 0 a d Example 3 Example 4 5.14. REFERENCES DOIGNON. J.-P •• Generalizations of interval orders. in E. Degreef and J. Van Buggenhaut (eds). T~ndS in MathematiaaZ PsyahoZogy. Elsevier Science Publishers B.V. (North-Holland), Amsterdam, 1984. FISHBURN. P.C., Intransitive indifference with unequal indifference intervals. J. Math. Psyaho.~ 7 (1970) 144-149. FISHBURN. P.C., Binary choice probabilities: on the varieties of stochastic transitivity. J. Math. Psyaho.~ 10 (1973) 327-352.

## Multicriteria Decision Aid and Artificial Intelligence

Author: Michael Doumpos
Publisher: John Wiley & Sons
ISBN: 1118522494
Format: PDF, ePub, Docs

Presents recent advances in both models and systems for intelligent decision making. Organisations often face complex decisions requiring the assessment of large amounts of data. In recent years Multicriteria Decision Aid (MCDA) and Artificial Intelligence (AI) techniques have been applied with considerable success to support decision making in a wide range of complex real-world problems. The integration of MCDA and AI provides new capabilities relating to the structuring of complex decision problems in static and distributed environments. These include the handling of massive data sets, the modelling of ill-structured information, the construction of advanced decision models, and the development of efficient computational optimization algorithms for problem solving. This book covers a rich set of topics, including intelligent decision support technologies, data mining models for decision making, evidential reasoning, evolutionary multiobjective optimization, fuzzy modelling, as well as applications in management and engineering. Multicriteria Decision Aid and Artificial Intelligence: Covers all of the recent advances in intelligent decision making. Includes a presentation of hybrid models and algorithms for preference modelling and optimisation problems. Provides illustrations of new intelligent technologies and architectures for decision making in static and distributed environments. Explores the general topics on preference modelling and learning, along with the coverage of the main techniques and methodologies and applications. Is written by experts in the field. This book provides an excellent reference tool for the increasing number of researchers and practitioners interested in the integration of MCDA and AI for the development of effective hybrid decision support methodologies and systems. Academics and post-graduate students in the fields of operational research, artificial intelligence and management science or decision analysis will also find this book beneficial.

## Fuzzy Multi Criteria Decision Making

Author: Cengiz Kahraman
Publisher: Springer Science & Business Media
ISBN: 0387768130
Format: PDF, ePub, Docs

This work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.

## Fuzzy Techniques for Decision Making

Author: José Carlos R. Alcantud
Publisher: MDPI
ISBN: 3038428876
Format: PDF

This book is a printed edition of the Special Issue "Fuzzy Techniques for Decision Making" that was published in Symmetry

## Organizational Psychology for Managers

Author: Stephen R Balzac
Publisher: Springer Science & Business Media
ISBN: 1461485053
Format: PDF, ePub, Mobi

## Fuzzy Optimization and Multi Criteria Decision Making in Digital Marketing

Author: Kumar, Anil
Publisher: IGI Global
ISBN: 1466688092
Format: PDF, Kindle

Abstract: "This book applies fuzzy theory and multi-criteria decision making principles for better practice in the digital business environment through the use of timely research and case studies on practical implementation of such theories in the digital marketplace"--Provided by publisher

## New Concepts and Trends of Hybrid Multiple Criteria Decision Making

Author: Gwo-Hshiung Tzeng
Publisher: CRC Press
ISBN: 1351680625
Format: PDF, Kindle

When people or computers need to make a decision, typically multiple conflicting criteria need to be evaluated; for example, when we buy a car, we need to consider safety, cost and comfort. Multiple criteria decision making (MCDM) has been researched for decades. Now as the rising trend of big-data analytics in supporting decision making, MCDM can be more powerful when combined with state-of-the-art analytics and machine learning. In this book, the authors introduce a new framework of MCDM, which can lead to more accurate decision making. Several real-world cases will be included to illustrate the new hybrid approaches.

## Multiperson Decision Making Models Using Fuzzy Sets and Possibility Theory

Author: Janusz Kacprzyk
Publisher: Springer Science & Business Media
ISBN: 9400921098
Format: PDF, Docs

Decision making is certainly a very crucial component of many human activities. It is, therefore, not surprising that models of decisions play a very important role not only in decision theory but also in areas such as operations Research, Management science, social Psychology etc . . The basic model of a decision in classical normative decision theory has very little in common with real decision making: It portrays a decision as a clear-cut act of choice, performed by one individual decision maker and in which states of nature, possible actions, results and preferences are well and crisply defined. The only compo nent in which uncertainty is permitted is the occurence of the different states of nature, for which probabilistic descriptions are allowed. These probabilities are generally assumed to be known numerically, i. e. as single probabili ties or as probability distribution functions. Extensions of this basic model can primarily be conceived in three directions: 1. Rather than a single decision maker there are several decision makers involved. This has lead to the areas of game theory, team theory and group decision theory. 2. The preference or utility function is not single valued but rather vector valued. This extension is considered in multiattribute utility theory and in multicritieria analysis. 3.