基于云重心平均树解法的动态联盟收益分配研究

Study on Profit Allocation of Dynamic Alliance Based on Average Tree Solution with Cloud Gravity Center

摘要:

针对传统收益分配方法不能很好地对具有交流结构限制的动态联盟收益进行分配,以及存在指标权重赋值主观性强等问题,通过结合图对策和云理论,提出了更为合理有效的收益分配方法。首先以传统平均树解法为分配基础,引入了风险承担度、合作努力度和资源投入度等收益影响因素,然后借鉴TOPSIS法的思想对云重心评价方法进行了改进,基于正负理想状态,确定了收益分配的修正系数,弥补了传统收益分配方法的不足。最后将云重心平均树解法应用到动态联盟收益分配的实例中,发现该方法的收益分配结果优于独立经营的结果,从而验证了该方法的合理性和可行性。

Abstract:

Considering that the traditional profit allocation method cannot allocate the profit of the dynamic alliance with limited communication structure commendably, and has strong subjectivity of index weight assignment, a more reasonable and effective profit distribution method is put forward by using graph theory and cloud theory. First, based on the traditional average tree solution, profit impact factors such as risk allocation, cooperative efforts and resources investment are introduced. And using the basic idea of TOPSIS method, the cloud gravity centroid judgement is improved. Then based on ideal and negative ideal state, the correction coefficient of the income distribution is determined, which makes up the traditional profit allocation method. Finally, the new method is applied to the example of dynamic alliance profit allocation. It is found that the profit distribution of the method is better than that of the independent operation, and the rationality and feasibility of the method is verified.