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Books > Computing & IT > General theory of computing
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Fuzzy Sets and Interactive Multiobjective Optimization (Paperback, Softcover reprint of the original 1st ed. 1993)
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Fuzzy Sets and Interactive Multiobjective Optimization (Paperback, Softcover reprint of the original 1st ed. 1993)
Series: Applied Information Technology
Expected to ship within 10 - 15 working days
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The main characteristics of the real-world decision-making problems
facing humans today are multidimensional and have multiple
objectives including eco nomic, environmental, social, and
technical ones. Hence, it seems natural that the consideration of
many objectives in the actual decision-making process re quires
multiobjective approaches rather than single-objective. One ofthe
major systems-analytic multiobjective approaches to decision-making
under constraints is multiobjective optimization as a
generalization of traditional single-objective optimization.
Although multiobjective optimization problems differ from single
objective optimization problems only in the plurality of objective
functions, it is significant to realize that multiple objectives
are often noncom mensurable and conflict with each other in
multiobjective optimization problems. With this ob servation, in
multiobjective optimization, the notion of Pareto optimality or
effi ciency has been introduced instead of the optimality concept
for single-objective optimization. However, decisions with Pareto
optimality or efficiency are not uniquely determined; the final
decision must be selected from among the set of Pareto optimal or
efficient solutions. Therefore, the question is, how does one find
the preferred point as a compromise or satisficing solution with
rational pro cedure? This is the starting point of multiobjective
optimization. To be more specific, the aim is to determine how one
derives a compromise or satisficing so lution of a decision maker
(DM), which well represents the subjective judgments, from a Pareto
optimal or an efficient solution set.
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