基于灰色绝对关联度的车货双边匹配决策研究

Research on the Decision-making Method of Vehicle-cargo Two-sided Matching Based on Grey Absolute Incidence Degree

针对含有灰色,模糊等不确定信息的车货供需双边匹配决策问题,利用灰色绝对关联度分析法测度匹配主体的满意度,建立基于匹配距离和匹配距离偏差最小的多目标灰色双边匹配模型,有效地设计车货供需匹配方案,提高双方主体的满意度和匹配率,运用线性加权法将多目标匹配模型转化为单目标优化模型,并通过MATLAB软件求解出最优匹配方案,利用算例验证了其可操作性和实用性。本文为车货供需匹配领域的研究提供了方法支撑,对提高我国公路货运物流效率具有现实意义。

With respect to the two-sided matching decision-making problems with grey and fuzzy information, based on matching distance and matching distance deviation, the thought and method of grey absolute incidence analysis is exploited to establish a two-sided matching decision-making model. It effectively designs the matching scheme of vehicle and cargo supply and demand, and improves the satisfaction and matching rate of the two-sided. The multi-objective matching model is transformed into a single-objective optimization model by a linear weighted method, and the optimal matching scheme is solved by MATLAB. And its operability and practicability are checked by an example. This paper provides method support for the research in the field of vehicle and cargo supply and demand matching and has practical significance for increasing the efficiency of highway freight logistics in China.