Fuzzy-Dominance and Its Application in Evolutionary Many Objective Optimization

Fuzzy-Dominance and Its Application in Evolutionary Many Objective Optimization
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DOI：
10.1109/cis.workshops.2007.184
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发表时间：
2007-12
期刊：
2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)
影响因子：
--
通讯作者：
Gaoping Wang;Huawei Jiang
Gaoping Wang;Huawei Jiang
中科院分区：
其他
文献类型：
--
作者：
Gaoping Wang;Huawei Jiang

文献摘要

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本文研究了Pareto优势关系的模糊化及其在进化多目标优化算法设计中的应用。提出了一种通用的排序方案，它以一种尺度无关、非对称和依赖于集合的方式为任意一组向量分配优势度。给出了基于模糊的最优解和支配解的不同定义。文中还给出了标准遗传算法的相应扩展--模糊优势遗传算法(FDGA)。为了验证该方法的有效性，在分析测试用例上对该方法进行了测试，以证明其有效性。
This paper studies the fuzzification of the Pareto dominance relation and its application to the design of Evolutionary Many-Objective Optimization algorithms. A generic ranking scheme is presented that assigns dominance degrees to any set of vectors in a scale- independent, nonsymmetric and set-dependent manner. Different fuzzy-based definitions of optimality and dominated solution are introduced. The corresponding extension of the Standard Genetic Algorithm, so-called Fuzzy-Dominance GA (FDGA), will be presented as well. To verify the usefulness of such an approach, the approach is tested on analytical test cases in order to show its validity.