Sequential Approximate Multiobjective Optimization Using Computational Intelligence - Couverture rigide
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Synopsis
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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Présentation de l'éditeur
This book highlights a new direction of multiobjective optimzation, which has never been treated in previous publications. When the function form of objective functions is not known explicitly as encountered in many practical problems, sequential appro
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence (Vector Optimization)
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence (Vector Optimization)
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Springer, 2009
ISBN 10 : 3540889094
ISBN 13 : 9783540889090
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
Edité par
Springer, 2009
ISBN 10 : 3540889094
ISBN 13 : 9783540889090
Ancien ou d'occasion
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Etat : Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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. N° de réf. du vendeur 4774859/1012
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
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Springer Berlin Heidelberg Mai 2009, 2009
ISBN 10 : 3540889094
ISBN 13 : 9783540889090
Neuf
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 216 pp. Englisch. N° de réf. du vendeur 9783540889090
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
Edité par
Springer, 2009
ISBN 10 : 3540889094
ISBN 13 : 9783540889090
Ancien ou d'occasion
Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
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Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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. N° de réf. du vendeur 4774859/1
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
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ISBN 10 : 3540889094
ISBN 13 : 9783540889090
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. No book on the subject so farSince no explicit functions form of objectives is available in many practical ( in particular, engineering design) problems, optimization using metamodels is very important in practiceBook is also a good applica. N° de réf. du vendeur 4901939
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
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Springer, Springer Spektrum Mai 2009, 2009
ISBN 10 : 3540889094
ISBN 13 : 9783540889090
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 216 pp. Englisch. N° de réf. du vendeur 9783540889090
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
Edité par
Springer, Springer Spektrum, 2009
ISBN 10 : 3540889094
ISBN 13 : 9783540889090
Neuf
Couverture rigide
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783540889090
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SEQUENTIAL APPROXIMATE MULTIOBJECTIVE OPTIMIZATION USING COMPUTATIONAL INTELLIGENCE (HB 2009)
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