Journal of Shanghai University（Natural Science Edition）
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YANG Yi1,2,PENG Zheng1，YAN Kan1，WU Dong-hua1
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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
CLC Number:
O 242.26〓〓〓
YANG Yi;PENG Zheng;YAN Kan;WU Dong-hua. Stochastic Level-Value Approximation for Global Optimization[J]. Journal of Shanghai University（Natural Science Edition）.
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URL: https://www.journal.shu.edu.cn/EN/
https://www.journal.shu.edu.cn/EN/Y2008/V14/I3/265
