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Multi-objective optimization based on meta-modeling by using support vector regression
Abstract Practical engineering design problems have a black-box objective function whose forms are not explicitly known in terms of design variables. In those problems, it is very important to make the number of function evaluations as few as possible in finding an optimal solution. So, in this paper, we propose a multi-objective optimization method based on meta-modeling predicting a form of each objective function by using support vector regression. In addition, we discuss a way how to select additional experimental data for sequentially revising a form of objective function. Finally, we illustrate the effectiveness of the proposed method through some numerical examples.
Multi-objective optimization based on meta-modeling by using support vector regression
Abstract Practical engineering design problems have a black-box objective function whose forms are not explicitly known in terms of design variables. In those problems, it is very important to make the number of function evaluations as few as possible in finding an optimal solution. So, in this paper, we propose a multi-objective optimization method based on meta-modeling predicting a form of each objective function by using support vector regression. In addition, we discuss a way how to select additional experimental data for sequentially revising a form of objective function. Finally, we illustrate the effectiveness of the proposed method through some numerical examples.
Multi-objective optimization based on meta-modeling by using support vector regression
Yun, Yeboon (author) / Yoon, Min (author) / Nakayama, Hirotaka (author)
Optimization and Engineering ; 10 ; 167-181
2008-11-06
15 pages
Article (Journal)
Electronic Resource
English
Multi-objective optimization , Pareto frontier , Support vector regression , Sequential approximation method , Evolutionary multi-objective optimization Mathematics , Optimization , Engineering, general , Systems Theory, Control , Environmental Management , Operation Research/Decision Theory , Financial Engineering
Multi-objective optimization based on meta-modeling by using support vector regression
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