期刊文献+

基于次微分集的外接长方体的不可微优化算法 被引量:1

An algorithm for solving nondifferentiable programming on circumscribed rectangular parallelepiped of subdifferentiable
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摘要 目的研究求解不可微优化问题的算法及收敛性。方法引进次微分集的外接长方体的概念,确定目标函数的下降方向。结果给出了一般的无约束不可微优化的一类可实现算法,并且证明了算法的收敛性,在一定的条件下算法还具有线性收敛性。结论初步的数值例子表明算法是有效的,且具有简单实用的特点。 Aim To research the algorithm for solving nondifferentiable programming. Methods Using a new concept of circumscribed rectangular parallelepiped to determine a decending direction of thetar function. Results A new algorithm of Nondifferentiable Optimization is given, and some results of convergence are proven. Conclusion Some numerical examples show that the algorithm is effective.
作者 王雪峰
出处 《西北大学学报(自然科学版)》 CAS CSCD 北大核心 2009年第2期196-198,共3页 Journal of Northwest University(Natural Science Edition)
基金 国家自然科学基金资助项目(60374063)
关键词 不可微规划 优化算法 次梯度 nondifferentiable programming algorithm subgradient
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参考文献3

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二级参考文献8

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同被引文献10

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