基于议题组合优化的虚拟企业成员协商模型研究

A combination optimization of related Issues negotiation model based on oglstic regression

协商与协作是虚拟企业最核心的内容,针对虚拟企业运行过程中不完全信息环境造成的企业成员间信息不对称,且随着虚拟企业运行产生的大量随机的、取值离散的多个协商议题而导致的协商有效性和适应性低下的问题,文章提出关注多个协商议题之间的关联属性,并形式化各个协商议题的属性表达,利用贝叶斯分类算法描述协商议题之间的取值和度量关联问题,基于Logistic回归算法刻画协商议题关联的决策边界,进而将多个协商议题进行优化组合。针对关联组合优化议题,兼顾考虑协商双方的效用最大化,构建虚拟企业成员多议题协商模型。对构建的协商模型进行仿真实验,实验结果表明,企业成员协商平均有效率约提高7%,协商平均适应度提高约5%,较好地促进了协商进程。

Because of the information asymmetry and disperse value of the negotiation issue under the incomplete information conditions, so the negotiation＇ s effectiveness and adaptability is poor. In order to improve this question, Paper pays attention to the relation of the multiple negotiation issues, try to describe the value of the relation of the multiple negotia- tion issues based on the Bayesian classifier and the decision boundary based on the Logistic regression, then get the com- bination optimization of related issues. For related combination optimization issue, think about the largest effect of the negotiation and get the best Pareto and create the negotiation model. The simulation results show that the average effec- tiveness increase 7% and the average adaptability increase 5%, so, the combination optimization negotiation model can promote the negotiation process.