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Modification Of Species-Based Differential Evolution For Multimodal Optimization

机译:多峰优化的种类基于物种的差分演化的修改

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At this time optimization has an important role in various fields as well as between other operational research, industry, finance and management. Optimization problem is the problem of maximizing or minimizing a function of one variable or many variables, which include unimodal and multimodal functions. Differential Evolution (DE), is a random search technique using vectors as an alternative solution in the search for the optimum. To localize all local maximum and minimum on multimodal function, this function can be divided into several domain of fitness using niching method. Species-based niching method is one of method that build sub-populations or species in the domain functions. This paper describes the modification of species-based previously to reduce the computational complexity and run more efficiently. The results of the test functions show species-based modifications able to locate all the local optima in once run the program.
机译:此时优化在各个领域以及其他操作研究,工业,金融和管理之间具有重要作用。优化问题是最大化或最小化一个变量或许多变量的函数的问题,包括单向和多模式函数。差分演进(DE)是一种随机搜索技术,使用矢量作为搜索最佳的替代解决方案。要本地化多模式功能的所有本地最大和最小值,可以使用幂幂方法分为几个适合域的域。基于物种的幂位方法是在域功能中构建子群或物种的方法之一。本文介绍了以前基于物种的修改,以降低计算复杂性并更有效地运行。测试功能的结果显示,基于物种的修改,能够在运行程序中定位所有本地Optima。

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