| 社会认识优化在非线性规划问题中的应用 |
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| 引用本文： | 苏俊霞.社会认识优化在非线性规划问题中的应用[J].计算机仿真,2007,24(9):261-264. |
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| 作者姓名： | 苏俊霞 |
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| 作者单位： | 南京工业大学信息科学与工程学院,江苏,南京,210009 |
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| 摘 要： | 社会认识优化(Society Cognitive Optimization,SCO)是一种基于社会认知理论提出的模拟人类社会的演化算法.社会认识优化是通过竞争选择和领域搜索来模拟社会认知理论中的社会学习能力,用代理来代表社会中的人,用知识库来代表社会中的知识,通过代理与知识库之间不断的交互来模拟人类的社会学习过程,从而达到优化学习的目的.命题逻辑中合取范式的可满足性(Satisfyability,SAT)问题是当代理论计算机科学的核心问题,是一典型的NP完全问题.可满足性问题的有效解决有着重要的理论意义和实际应用价值.文中将社会认识优化算法应用于求解可满足性问题,得到了比较满意的结果.
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| 关 键 词： | 演化算法 社会认识优化 可满足性问题 模拟社会 认识 优化算法 线性规划问题 应用 Problems Nonlinear Programming Optimization Cognitive 结果 比较 求解 价值 意义 理论计算机科学 有效解决 可满足性问题 完全问题 核心 范式 |
| 文章编号： | 1006-9348（2007）09-0261-04 |
| 修稿时间： | 2006-06-28 |
The Social Cognitive Optimization Applied in Nonlinear Programming Problems |
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| SU Jun-xia.The Social Cognitive Optimization Applied in Nonlinear Programming Problems[J].Computer Simulation,2007,24(9):261-264. |
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| Authors: | SU Jun-xia |
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| Affiliation: | College of Information Science and Engineering, Nanjing University of Technology, Nanjing Jiangsu 210009, China |
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| Abstract: | Society Cognitive Optimization(SCO) is a kind of evolutionary algorithm for simulatiing human society based on Society Cognitive Theory(SCT).SCO simulates the social learning capability in SCT through tournament selection and neighborhood searching.Using agent to represent person and library to represent knowledge,and through the interaction between agent and library,SCO simulates the human's learning process to achieve optimization.The satisfyability(SAT) problem of conjunction normal form is the core of contemporary theoretical computer science and it's a typical NP-complete problem.So solving the SAT problem effectively has important academic significance and practical application value.And then,this paper applied SCO to solve the SAT problem and the result is good. |
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| Keywords: | Evolutionary algorithm Society cognitive optimization(SCO) Satisfyability problem |
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