Journal of the Operations Research Society of China ›› 2018, Vol. 6 ›› Issue (3): 429-444.doi: https://doi.org/10.1007/s40305-017-0175-1

所属专题: Continuous Optimization

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  • 出版日期:2018-09-30 发布日期:2018-09-30

A Stochastic Level-Value Estimation Method for Global Optimization

Hong-Bin Yu1 , Wei-Jia Zeng2 , Dong-Hua Wu3   

  1. 1 Department of Basic, Shanghai Vocational College of Science and Technology,Shanghai 201800, China
    2 Department of Computer Engineering and Science, Shanghai University, Shanghai 200444,China
    3 Department of Mathematics, Shanghai University, Shanghai 200444, China
  • Online:2018-09-30 Published:2018-09-30

Abstract:

In this paper, we propose a stochastic level-value estimation method to solve a kind of box-constrained global optimization problem. For this purpose, we first derive a generalized variance function associated with the considered problem and prove that the largest root of the function is the global minimal value. Then, Newton’s method is applied to find the root. The convergence of the proposed method is established under some suitable conditions. Based on the main idea of the cross-entropy method to update the sampling density function, an important sampling technique is proposed in the implementation. Preliminary numerical experiments indicate the validity of the proposed method.

Key words: Global optimization ·, Level-value estimation ·, Generalized variance function ·, Cross-entropy method