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Simulated Annealing as a Global Optimization Algorithm Used in Numerical Prototyping of Electronic Packaging

机译:模拟退火作为电子包装数值原型中的全局优化算法

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There are many optimization algorithms, which can be used to find the extremum of a function. However, in optimizing the function, which is obtained from the numerical calculations, it is necessary to apply the proper global optimization algorithm. It is caused by the high nonlinearity of the numerical function's response. The nonlinear function with not known analytical form may have many local extrema and only one global extremum. Such problems occur in numerical prototyping, when the finite element method is used, for example in numerical optimization in electronic packaging in order to inmprove the component's reliability. There is a group of optimization methods, which can solve such nonlinear problem with success. These methods are capable to avoid of being trapped in local extremum. To this group belongs: simulated annealing, evolutionary algorithms, tabu search, ant search, etc. In this paper the simulated annealing algorithm is described and applied to optimize the electronic passive elements.
机译:有许多优化算法,可用于找到函数的极值。然而,在优化从数值计算获得的函数时,必须应用适当的全局优化算法。它是由数值函数响应的高非线性引起的。非已知分析形式的非线性功能可能有许多局部极值,只有一个全球极值。当使用有限元方法时,在数值原型中发生这种问题,例如在电子包装中的数值优化中,以便进入组件的可靠性。有一组优化方法,可以解决此类非线性问题。这些方法能够避免被困在局部极值中。本组属于:在本文中,模拟退火,进化算法,禁忌搜索,蚂蚁搜索等。描述并应用模拟退火算法以优化电子无源元件。

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