Social network analysis is explicitly interested in the relationships among social actors. Focusing on structural variables, it opens up a field of data analysis and model building which is completely different from c...Social network analysis is explicitly interested in the relationships among social actors. Focusing on structural variables, it opens up a field of data analysis and model building which is completely different from conventional social statistical methods. Spanning nearly seventy years of research, statistical network analysis has witnessed three stages of models. Beginning from the late 1930s, the first generation of scholars (Moreno, Katz, Heider, etc.) studied the distribution of various network statistics. The second stage began from the 1970s and continued to the mid 1980s. It dealt primarily with exponential family of probability distributions for directed graphs (p 1 model) under the vital assumption of “dyad independence”. Relaxing this assumption, Frank and Strauss (1986), Strauss and Ikeda (1990), Wasserman and Pattison (1996) published their pathbreaking papers based on Markov’s random graphs models (p\+* model and its generalization: logit p\+*), which brought social network models to a new stage. It is an extremely flexible and complete model dealing with all sorts of structural aspects of social networks. This substantial “real” structural research should be employed to examine the relational essence of Chinese society.展开更多
新产品研发过程中资源合理优化配置程度影响着研发周期的长短。以缩短研发周期为目标,构建了多技能资源项目调度问题模型,在蚁群优化算法基础上引入区块模型,建立了一种基于区块模型的蚁群算法,提出了一种分层编码策略用于解决活动的优...新产品研发过程中资源合理优化配置程度影响着研发周期的长短。以缩短研发周期为目标,构建了多技能资源项目调度问题模型,在蚁群优化算法基础上引入区块模型,建立了一种基于区块模型的蚁群算法,提出了一种分层编码策略用于解决活动的优先关系约束问题,采用串行调度生成机制提高初始解质量。使用改造后的PSPLIB(Project Scheduling Problem Library)算例进行测试并与其他算法比较,仿真结果表明:对于小规模问题,该算法可获得精确度非常高的可行解且收敛速度更快;对于大规模问题,该算法在提高求解质量和求解速度方面同样具有良好的性能。展开更多
文摘Social network analysis is explicitly interested in the relationships among social actors. Focusing on structural variables, it opens up a field of data analysis and model building which is completely different from conventional social statistical methods. Spanning nearly seventy years of research, statistical network analysis has witnessed three stages of models. Beginning from the late 1930s, the first generation of scholars (Moreno, Katz, Heider, etc.) studied the distribution of various network statistics. The second stage began from the 1970s and continued to the mid 1980s. It dealt primarily with exponential family of probability distributions for directed graphs (p 1 model) under the vital assumption of “dyad independence”. Relaxing this assumption, Frank and Strauss (1986), Strauss and Ikeda (1990), Wasserman and Pattison (1996) published their pathbreaking papers based on Markov’s random graphs models (p\+* model and its generalization: logit p\+*), which brought social network models to a new stage. It is an extremely flexible and complete model dealing with all sorts of structural aspects of social networks. This substantial “real” structural research should be employed to examine the relational essence of Chinese society.
文摘新产品研发过程中资源合理优化配置程度影响着研发周期的长短。以缩短研发周期为目标,构建了多技能资源项目调度问题模型,在蚁群优化算法基础上引入区块模型,建立了一种基于区块模型的蚁群算法,提出了一种分层编码策略用于解决活动的优先关系约束问题,采用串行调度生成机制提高初始解质量。使用改造后的PSPLIB(Project Scheduling Problem Library)算例进行测试并与其他算法比较,仿真结果表明:对于小规模问题,该算法可获得精确度非常高的可行解且收敛速度更快;对于大规模问题,该算法在提高求解质量和求解速度方面同样具有良好的性能。
