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A Globally Convergent Algorithm with Adaptively Refined Discretization for Semi-Infinite Optimization Problems Arising in Engineering Design.

机译:工程设计中出现的半无限优化问题的自适应细化离散化全局收敛算法。

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摘要

Optimization problems arising in engineering design often exhibit specific features which, in the interest of computational efficiency, ought to be exploited. Such is the possible presence of 'functional' specifications, i.e., specifications that are to be met over an interval of values of an independent parameter such as time or frequency. Such problems pertain to semiinfinite optimization. While most of the algorithms that have been proposed for the solution of these problems make use, at each iteration, of a set of local maximizers over the range of the independent parameter, the question of suitably approximating such maximizers is generally left aside. It has been suggested that this issue can be addressed by means of an adaptively refined discretization of the interval of variation of the independent parameter. The algorithm proposed in this paper makes use of such a technique and, by means of a certain memory mechanism, avoids the potential lack of convergence suffered by an existing algorithm.
机译:工程设计中出现的优化问题通常表现出特定的特征,为了提高计算效率,应该利用这些特征。这就是可能存在的“功能性”规范,即在独立参数的值(例如时间或频率)的值的间隔内要满足的规范。这些问题与半无限优化有关。虽然为解决这些问题而提出的大多数算法在每次迭代中都使用了独立参数范围内的一组局部最大化器,但通常不考虑适当近似此类最大化器的问题。已经提出,可以通过独立参数变化间隔的自适应细化离散化来解决该问题。本文提出的算法利用了这种技术,并通过某种存储机制,避免了现有算法可能存在的收敛性不足。

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  • 作者

    Panier, E.R.; Tits, A.L.;

  • 作者单位
  • 年度 1988
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  • 原文格式 PDF
  • 正文语种 en_US
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