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首页> 外文会议>Computer Science and Software Engineering, CSSE 2008, 2008 International Conference on >Two Dimensions Simplex Evolution Algorithm
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Two Dimensions Simplex Evolution Algorithm

机译：二维单纯形演化算法

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摘要

Under the basic frame of evolution computations (EA) and the kernel idea of Nelder-Mead simplex method, a novel evolution algorithm (EA), namely the two dimensions simplex EA (2D-simplexEA), is proposed. 2D-SimplexEA has four search operators: a reflection operator, a contraction operator, a plane search operator and a mutation operator. The first three operators and the forth operators are applied to the worst vertex and the best vertex respectively in order to reproduce a better vertex. The priority of the three operators for the worst vertex is the reflection operator, the contraction operator and the plane search operator, because there is a strong possibility that the reflection operator and the contraction operator can find out a new vertex better than the worst vertex along the optimal search direction of Nelder-Mead simplex method. When neither of them finds out a better vertex, the plane search operator is effective. It is the most important means for the best vertex to be improved by mutation without the other effective information and approaches. The numerical experiments verify 2D-SimplexEA correct and effective.
机译：在进化计算（EA）的基本框架和Nelder-Mead单纯形法的核心思想的基础上，提出了一种新的进化算法（EA），即二维单纯形EA（2D-simplexEA）。 2D-SimplexEA具有四个搜索运算符：反射运算符，收缩运算符，平面搜索运算符和变异运算符。前三个运算符和第四个运算符分别应用于最差的顶点和最佳的顶点，以便再现更好的顶点。对于最差顶点，这三个算子的优先级是反射算子，收缩算子和平面搜索算子，因为很可能反射算子和收缩算子可以找到比最差顶点更好的新顶点。 Nelder-Mead单纯形法的最佳搜索方向。当他们两个都找不到更好的顶点时，平面搜索算子将是有效的。这是在没有其他有效信息和方法的情况下通过突变改善最佳顶点的最重要方法。数值实验验证了2D-SimplexEA的正确性和有效性。

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