GENERATION OF PARETO FRONTIERS USING SUPPORT VECTOR MACHINE
GENERATION OF PARETO FRONTIERS USING SUPPORT VECTOR MACHINE
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发表时间：
2004
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通讯作者：
Y. Yun;H. Nakayama;M. Arakawa
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文献类型：
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作者：
Y. Yun;H. Nakayama;M. Arakawa
总结：使用计算智能的近似方法，例如，进化算法已经被应用于多目标优化问题。为了更精确地产生大量的近似Pareto最优解，这些方法得到了不断的改进。提出了一种利用支持向量机求解多目标优化问题的近似Pareto前沿的新方法。将该方法与进化算法相结合，可以生成很好的近似Pareto前沿，并且可以在可视化Pareto前沿的基础上方便地进行两个或三个目标函数的决策。最后，通过几个数值例子说明了所提出的方法的有效性。
Summary: Approximation methods using computational intelligence, for example, evolutionary algorithms have been applied to multi-objective optimization problems. Those methods have been improved increasingly in order to generate more exactly a lot of approximate Pareto optimal solutions. This paper proposes a new method using support vector machine to find an approximate Pareto frontier in multi-objective optimization problems. Furthermore, this paper shows that combining the proposed method and evolutionary algorithm can generate well approximate Pareto frontier, and a decision making with two or three objective functions can be easily performed on the basis of visualized Pareto frontiers by the proposed method. Finally, the effectiveness of the proposed method will be illustrated through several numerical examples.