| 求解随机线性互补问题的社会认知算法 |
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| 引用本文： | 李蕊.求解随机线性互补问题的社会认知算法[J].西安工业大学学报,2012,32(11):870-873. |
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| 作者姓名： | 李蕊 |
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| 作者单位： | 西安工业大学理学院,西安,710021 |
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| 摘 要： | 针对传统算法求解随机线性互补问题时需要给定初始点、计算梯度,并且解不唯一时无法获得多个最优解的困难,提出了求解随机线性互补问题的社会认知算法.将随机线性互补问题转化为含有随机变量的约束优化问题,并通过平均抽样逼近该随机约束优化问题,利用社会认知算法求解该优化问题.数值试验结果表明社会认知算法是求解随机线性互补问题的有效算法.
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| 关 键 词： | 随机线性互补问题 平均抽样逼近 智能优化算法 社会认知算法 |
Social Cognitive Optimization Algorithm for Solving Stochastic Linear Complementarity Problem |
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| Authors: | LI Rui |
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| Affiliation: | LI Rui (School of Science, Xi＇an Technological University,Xi＇an 710021, China) |
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| Abstract: | When the classical algorithms are used to solve the stochastic linear complementarity problem,it is necessary to select the initial point and calculte the gradient, and it is hard to obtain optimal solutions if three are no only solution. Because of the weaknesses of the classical algorithms, the paper presents the social cognitive optinization method. The stochastic linear complementarity problem is |
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| Keywords: | stochastic linear complementarity problem sample average approximation intelligent optimization algorithm social cognitive optimization algorithm |
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