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.