基于熵-层次分析法的智能物流驾驶员评价系统设计

Xiuhui Wang, Xiaoyu Ma, Jing Fan, Qiongwei Ye
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引用次数: 2

摘要

本文在分析当前物流绩效评价研究现状的基础上,结合x公司的实际运营模式,将可能影响配送绩效评价的所有因素进行整合,最终选取11个指标对驱动因素进行综合绩效评价。这些指标分为四个方面:总工作量、运输质量、服务水平和执行。采用熵权法和层次分析法确定各指标的综合权重,并引入区域因子丰富了权重。此外,在评价模型中加入了驾驶员个人的相对进步因子,以更好地衡量驾驶员的努力程度。在对x公司的实证分析中,通过与以往绩效评价结果的对比,检验了模型的合理性和可执行性。结果表明,改进后的模型能够充分反映物流司机的绩效,并对物流司机进行有效区分。同时,该模型可以为后续的薪酬考核和任务分配优先级提供依据。更重要的是,这对于鼓励驾驶员按照算法指令执行任务具有现实意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of Intelligent Logistics Drivers Evaluation System-Based on Entropy-AHP Method
Based on the analysis of current research in performance evaluation of logistics and the practical operation mode of x company, this paper integrates all the factors that may affect performance evaluation of distribution and finally selects 11 indicators to make a comprehensive performance evaluation of drivers. These indicators are classified as four dimensions: total amount of work, transportation quality, service level and execution. Entropy weight method and analytic hierarchy process (AHP) are adopted to determine the comprehensive weight of each indicator, which is also enriched by the introduction of region factor. Besides, the drivers' individual relative progress factor is added into this evaluation model to better measure their efforts. In the empirical analysis of x company, the rationality and performability of the model are tested by comparing with the previous performance evaluation result. The result showed that this improved model could fully reflect the performance of logistics drivers and make effective distinctions between them. Also, this model can provide a basis for subsequent salary assessment and task allocation priority. What's more, it has practical significance for encouraging drivers to carry out tasks obeying the algorithm instructions.
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