模糊优势及其在进化多目标优化中的应用

2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007) Pub Date : 2007-12-15 DOI:10.1109/CIS.WORKSHOPS.2007.184

Gaoping Wang, Huawei Jiang

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引用次数: 72

摘要

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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Fuzzy-Dominance and Its Application in Evolutionary Many Objective Optimization

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.

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来源期刊

2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)

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