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Multiobjective Optimization: Behavioral and Computational Considerations (Paperback, Softcover reprint of the original 1st ed. 1992)
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Multiobjective Optimization: Behavioral and Computational Considerations (Paperback, Softcover reprint of the original 1st ed. 1992)
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Throughout the development of mathematical programming researchers
have paid great attention to problems that are described by a
single objective that can only be achieved subject to satisfying a
set of restrictions or constraints. Recently, it has been
recognized that the use of a single objective limits the
applicability of In reality, many multiobjective mathematical
programming models. situations exist and frequently these mUltiple
objectives are in direct conflict. Research on multiobjective
problems can be broken down into two broad categories:
multiobjective optimization and multicriterion decision theory.
Multiobjective optimization models are based on techniques such as
linear programming. In general, the multiobjective optimization
problem can be defined as finding a feasible alternative that
yields the most preferred set of values for the objective
functions. This problem differs from a single objective because
subjective methods are required to determine which alternative is
most preferred. A body of literature parallel to that m
multiobjective optimization has been developing in the area of
multicriterion decision theory. These models are based on classical
decision analysis, particularly utility theory. One focus of this
research has been the development and testing of procedures for
estimating multiattribute utility functions that are consistent
with rational decision maker behavior. A utility function provides
a model of a decision maker's choice among alternatives. This
literature is directly xii MULTIOBJECTIVE OPTIMIZATION applicable
to multiobjective optimization and provides much needed insight
into the subjective character of that problem.
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