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Fuzzy Preference Ordering of Interval Numbers in Decision Problems (Studies in Fuzziness and Soft Computing, Band 238) - Softcover

Buch 45 von 183: Studies in Fuzziness and Soft Computing

Sengupta, Atanu; Pal, Tapan Kumar

 
9783642100604: Fuzzy Preference Ordering of Interval Numbers in Decision Problems (Studies in Fuzziness and Soft Computing, Band 238)

Inhaltsangabe

In conventional mathematical programming, coefficients of problems are usually determined by the experts as crisp values in terms of classical mathematical reasoning. But in reality, in an imprecise and uncertain environment, it will be utmost unrealistic to assume that the knowledge and representation of an expert can come in a precise way. The wider objective of the book is to study different real decision situations where problems are defined in inexact environment. Inexactness are mainly generated in two ways – (1) due to imprecise perception and knowledge of the human expert followed by vague representation of knowledge as a DM; (2) due to huge-ness and complexity of relations and data structure in the definition of the problem situation. We use interval numbers to specify inexact or imprecise or uncertain data. Consequently, the study of a decision problem requires answering the following initial questions: How should we compare and define preference ordering between two intervals?, interpret and deal inequality relations involving interval coefficients?, interpret and make way towards the goal of the decision problem?

The present research work consists of two closely related fields: approaches towards defining a generalized preference ordering scheme for interval attributes and approaches to deal with some issues having application potential in many areas of decision making.

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Über die Autorin bzw. den Autor

Dr Atanu Sengupta is a Professor at the Department of Economics, Burdwan University, West Bengal, India, where he has been teaching for more than a decade. He obtained his Ph.D. from the Economic Research Unit, Indian Statistical Institute (ISI), Kolkata. He has published over 45 papers in various refereed national and international journals such as Economic and Political Weekly, Sankhya, Social Indicators Research, International Journal of Education and Development, Indian Economic Review, Asia Pacific Development Journal, and Asia Pacific Journal of Education and Development, and has also contributed chapters in various edited volumes. He also published eight books, including two edited volumes. He is a regular reviewer for several reputed national and international journals. His areas of interest include econometrics, financial economics, development economics, microeconomics and growth theory. Dr Sanjoy De is anAssistant Professor, Shyampur Siddheswari Mahavidyalaya, under the University of Calcutta, West Bengal, India. Previously, he served as Lead Analyst in Zacks Investment Research in Kolkata and as Senior Analyst at ICFAI University Press, Hyderabad, India. He obtained his Ph.D. in Economics from Burdwan University, Burdwan, West Bengal, India. At ICFAI, he was responsible for writing numerous articles on business, finance and economics. He has also published papers in Indian Economic Journal, Journal of Income and Wealth, Mainstream Weekly and others. His areas of interest include banking, microeconomics and statistics.

Von der hinteren Coverseite

In conventional mathematical programming, coefficients of problems are usually determined by the experts as crisp values in terms of classical mathematical reasoning. But in reality, in an imprecise and uncertain environment, it will be utmost unrealistic to assume that the knowledge and representation of an expert can come in a precise way. The wider objective of the book is to study different real decision situations where problems are defined in inexact environment. Inexactness are mainly generated in two ways – (1) due to imprecise perception and knowledge of the human expert followed by vague representation of knowledge as a DM; (2) due to huge-ness and complexity of relations and data structure in the definition of the problem situation. We use interval numbers to specify inexact or imprecise or uncertain data. Consequently, the study of a decision problem requires answering the following initial questions – How should we

  • compare and define preference ordering between two intervals?
  • interpret and deal inequality relations involving interval coefficients?
  • interpret and make way towards the goal of the decision problem?

The present research work consists of two closely related fields: approaches towards defining a generalized preference ordering scheme for interval attributes and approaches to deal with some issues having application potential in many areas of decision making.

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Weitere beliebte Ausgaben desselben Titels

9783540899143: Fuzzy Preference Ordering of Interval Numbers in Decision Problems (Studies in Fuzziness and Soft Computing, 238, Band 238)

Vorgestellte Ausgabe

ISBN 10:  3540899146 ISBN 13:  9783540899143
Verlag: Springer, 2009
Hardcover