摘要
针对第三方物流供应商评价指标数据的不确定性和高维性,为克服以往评价方法的不足,提出了综合评价的基于实数编码加速遗传投影寻踪方法。采用投影寻踪模型将高维数据投影到低维子空间上,并对数据结构进行分析;采用基于实数编码的加速遗传算法优化投影方向,克服了投影寻踪模型最佳投影方向难于寻找或容易陷入局部最优的问题;通过最佳投影方向来判断各评价指标对综合评价目标的影响程度和方向,得出投影指标值从大到小的排序。同时,对物流供应商做深入分析,将这一方法用于对低维数据(二级指标)进行评价排序,结果显示与综合评价基本一致,达到了对第三方物流供应商科学、准确的评价,可为企业正确选择物流供应商提供依据。
In order to overcome the lack of previous evaluation methods,we suggest Projection Pursuit method based on Real-coded Accelerating Genetic Algorithm for the uncertain and high -dimensional nature of the evaluation indicator data of TPL providers. Projecting the high -dimensional data onto the low-dimensional sub-space by PP model and then analyzing the data structure,optimizing the projection direction by using RAGA to overcome the difficulty of finding the best projection direction or the problem of falling into local optimum,the paper determines the extent of impacting and the direction of the evaluation indicators on comprehensive evaluation target and calculates the sort of the projection index value in descending order. Furthermore,we try to use this method on low -dimensional data to analyze logistics providers deeply and the results show that basically consistent with the comprehensive evaluation. We achieve scientific and accurate evaluation to TPL providers and can provide a basis for the enterprise to select a logistics provider.
出处
《哈尔滨工业大学学报(社会科学版)》
2010年第2期89-94,共6页
Journal of Harbin Institute of Technology(Social Sciences Edition)
基金
国家自然科学基金(70672117)