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Books > Science & Mathematics > Mathematics > Optimization
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence (Hardcover, 2009 ed.)
Loot Price: R4,019
Discovery Miles 40 190
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence (Hardcover, 2009 ed.)
Series: Vector Optimization
Expected to ship within 18 - 22 working days
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Many kinds of practical problems such as engineering design,
industrial m- agement and ?nancial investment have multiple
objectives con?icting with eachother.
Thoseproblemscanbeformulatedasmultiobjectiveoptimization. In
multiobjective optimization, there does not necessarily a unique
solution which minimizes (or maximizes) all objective functions. We
usually face to the situation in which if we want to improve some
of objectives, we have to give up other objectives. Finally, we pay
much attention on how much to improve some of objectives and
instead how much to give up others. This is called "trade-o?. "
Note that making trade-o? is a problem of value ju- ment of
decision makers. One of main themes of multiobjective optimization
is how to incorporate value judgment of decision makers into
decision s- port systems. There are two major issues in value
judgment (1) multiplicity of value judgment and (2) dynamics of
value judgment. The multiplicity of value judgment is treated as
trade-o? analysis in multiobjective optimi- tion. On the other
hand, dynamics of value judgment is di?cult to treat. However, it
is natural that decision makers change their value judgment even in
decision making process, because they obtain new information during
the process. Therefore, decision support systems are to be robust
against the change of value judgment of decision makers. To this
aim, interactive p-
grammingmethodswhichsearchasolutionwhileelicitingpartialinformation
on value judgment of decision makers have been developed. Those
methods are required to perform ?exibly for decision makers'
attitude.
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