Fuzzy-Dominance and Its Application in Evolutionary Many Objective Optimization

Gaoping Wang, Huawei Jiang
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引用次数: 72

Abstract

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.
模糊优势及其在进化多目标优化中的应用
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。提出了一种以尺度无关、非对称和集相关的方式对任意向量集分配优势度的通用排序方案。介绍了基于模糊的最优性和支配解的不同定义。标准遗传算法的相应扩展,即所谓的模糊优势遗传算法(FDGA),也将被提出。为了验证这种方法的有效性,在分析测试用例上对该方法进行了测试,以显示其有效性。
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