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Titlebook: Sequential Approximate Multiobjective Optimization Using Computational Intelligence; Min Yoon,Yeboon Yun,Hirotaka Nakayama Book 2009 Sprin

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发表于 2025-3-21 19:53:53 | 显示全部楼层 |阅读模式
书目名称Sequential Approximate Multiobjective Optimization Using Computational Intelligence
编辑Min Yoon,Yeboon Yun,Hirotaka Nakayama
视频video
概述No book on the subject so far.Since no explicit functions form of objectives is available in many practical ( in particular, engineering design) problems, optimization using metamodels is very importa
丛书名称Vector Optimization
图书封面Titlebook: Sequential Approximate Multiobjective Optimization Using Computational Intelligence;  Min Yoon,Yeboon Yun,Hirotaka Nakayama Book 2009 Sprin
描述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 mak
出版日期Book 2009
关键词Evolutionary Multi-Objective Optimization; Machine Learning; Meta-Modelling; Optimal Design of Experime
版次1
doihttps://doi.org/10.1007/978-3-540-88910-6
isbn_softcover978-3-642-10030-7
isbn_ebook978-3-540-88910-6Series ISSN 1867-8971 Series E-ISSN 1867-898X
issn_series 1867-8971
copyrightSpringer-Verlag Berlin Heidelberg 2009
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发表于 2025-3-21 22:33:52 | 显示全部楼层
Basic Concepts of Multi-objective Optimization,of twentieth century, while a mathematical development was made by Cantor at almost the same ages. Today, we usually refer a solution of multiobjective optimization to as a Pareto solution. Scalarization techniques for multiple objective functions are already presented in Edgeworth’s book more than
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Sequential Approximate Optimization,f design variables, under this circumstance, the value of objective functions is obtained by some analysis such as structural analysis, fluid mechanic analysis, and thermodynamic analysis. Usually, these analyses are considerably time consuming to obtain a value of objective functions. In order to m
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Engineering Applications,ce in collaborating with Japanese industrial companies. Some of major difficulties in engineering problems are (1) we have many (sometimes, a large number of) objective functions and (2) the function form of criteria is black box, namely cannot be explicitly given in terms of design variables.
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