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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