知识转移对群体决策偏好收敛速度的影响
发布时间：2019-02-20 09:48
【摘要】：群体决策往往是一个动态过程,个体间的知识转移会使决策者的偏好改变,因此对决策过程进行动态考量更切合实际。提出了基于惯性粒子群算法的偏好收敛模型,探讨知识转移对群体决策动态偏好收敛过程的影响。将知识分为内部自有知识和外部转移知识,分别讨论了这两类知识及不同知识转移量对偏好收敛速度产生的影响,并对比分析了确定与随机因素条件下收敛次数的差异。结果表明在其他条件相同的情况下,如果群体内知识转移速度越大,那么群体最终达成观点一致性的程度越高。随机性模型比确定性模型经过更多次的仿真步长才能达到群体观点一致收敛。计算实例表明本文提出的偏好收敛动态模型可应用于员工绩效考核,能够为动态群体决策偏好收敛分析和评价提供依据。
[Abstract]:Group decision making is often a dynamic process, and the knowledge transfer between individuals will change the preference of decision makers, so it is more practical to consider the decision-making process dynamically. A preference convergence model based on inertial particle swarm optimization is proposed, and the influence of knowledge transfer on the dynamic preference convergence process of group decision making is discussed. The knowledge is divided into internal knowledge and external knowledge. The effects of these two kinds of knowledge and different amount of knowledge transfer on the convergence rate of preference are discussed, and the difference of convergence times between determined and random factors is analyzed. The results show that under the same conditions, if the speed of knowledge transfer within the group is greater, the degree of consensus is higher. The stochastic model has more simulation steps than the deterministic model in order to converge uniformly. The calculation example shows that the proposed dynamic model of preference convergence can be applied to employee performance appraisal and can provide the basis for the analysis and evaluation of preference convergence in dynamic group decision making.
【作者单位】： 华南理工大学工商管理学院;
【基金】：广东省自然科学基金资助项目(8151064101000007) 广东省教育厅人文社会科学研究创新团队项目(B16N908002f)
【分类号】：C934
本文编号：2427063
[Abstract]:Group decision making is often a dynamic process, and the knowledge transfer between individuals will change the preference of decision makers, so it is more practical to consider the decision-making process dynamically. A preference convergence model based on inertial particle swarm optimization is proposed, and the influence of knowledge transfer on the dynamic preference convergence process of group decision making is discussed. The knowledge is divided into internal knowledge and external knowledge. The effects of these two kinds of knowledge and different amount of knowledge transfer on the convergence rate of preference are discussed, and the difference of convergence times between determined and random factors is analyzed. The results show that under the same conditions, if the speed of knowledge transfer within the group is greater, the degree of consensus is higher. The stochastic model has more simulation steps than the deterministic model in order to converge uniformly. The calculation example shows that the proposed dynamic model of preference convergence can be applied to employee performance appraisal and can provide the basis for the analysis and evaluation of preference convergence in dynamic group decision making.
【作者单位】： 华南理工大学工商管理学院;
【基金】：广东省自然科学基金资助项目(8151064101000007) 广东省教育厅人文社会科学研究创新团队项目(B16N908002f)
【分类号】：C934
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