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dbr:Metaheuristic
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dbr:Social_cognitive_optimization
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社会认知优化 Social cognitive optimization
rdfs:comment
社会认知优化（Social Cognitive Optimization, SCO），又称社会认识优化算法、社会认知算法。它是一种基于社会认知理论的群体智能优化算法。 SCO算法已经被应用于非线性规划问题，布尔可满足性问题，软件可靠性分配问题，自动机制设计等。 Social cognitive optimization (SCO) is a population-based metaheuristic optimization algorithm which was developed in 2002. This algorithm is based on the social cognitive theory, and the key point of the ergodicity is the process of individual learning of a set of agents with their own memory and their social learning with the knowledge points in the social sharing library. It has been used for solving continuous optimization, integer programming, and combinatorial optimization problems. It has been incorporated into the NLPSolver extension of Calc in Apache OpenOffice.
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社会认知优化（Social Cognitive Optimization, SCO），又称社会认识优化算法、社会认知算法。它是一种基于社会认知理论的群体智能优化算法。 SCO算法已经被应用于非线性规划问题，布尔可满足性问题，软件可靠性分配问题，自动机制设计等。 Social cognitive optimization (SCO) is a population-based metaheuristic optimization algorithm which was developed in 2002. This algorithm is based on the social cognitive theory, and the key point of the ergodicity is the process of individual learning of a set of agents with their own memory and their social learning with the knowledge points in the social sharing library. It has been used for solving continuous optimization, integer programming, and combinatorial optimization problems. It has been incorporated into the NLPSolver extension of Calc in Apache OpenOffice.
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