一种全局优化的随机水平值逼近算法

上海大学学报(自然科学版)

一种全局优化的随机水平值逼近算法

杨毅1，2，彭拯1，严侃1，邬冬华1

1.上海大学理学院，上海 200444；2.丽水学院数学系，浙江丽水 323000

收稿日期:2007-09-18 修回日期:1900-01-01 出版日期:2008-06-30 发布日期:2008-06-30
通讯作者: 邬冬华

Stochastic Level-Value Approximation for Global Optimization

YANG Yi1,2,PENG Zheng1，YAN Kan1，WU Dong-hua1

1.College of Sciences, Shanghai University, Shanghai 200444, China;
2.Department of Mathematics, Lishui College, Lishui 323000, Zhejiang, China

Received:2007-09-18 Revised:1900-01-01 Online:2008-06-30 Published:2008-06-30
Contact: WU Dong-hua

摘要/Abstract

摘要： 对一类在闭箱上处处有定义的单峰目标函数的全局优化问题,提出一种随机水平值逼近算法,证明了算法的渐近收敛性.数值结果验证了算法的有效性.

关键词: 渐近收敛性, 全局优化, 随机水平值逼近

Abstract:

We propose a stochastic level-value approximating method (SLVAM) for
global optimization problem that is defined in an entire box. We discuss and establish a sufficient condition for the global optimality in probability measure
, and prove that the SLVAM algorithm is convergent in probability. Numerical results show its effectiveness.

Key words: convergence in probability, stochastic level-value approximation, global optimization

中图分类号:

O 242.26〓〓〓

杨毅;彭拯;严侃;邬冬华. 一种全局优化的随机水平值逼近算法[J]. 上海大学学报(自然科学版).

YANG Yi;PENG Zheng;YAN Kan;WU Dong-hua. Stochastic Level-Value Approximation for Global Optimization
[J]. Journal of Shanghai University（Natural Science Edition）.