基于空间聚类算法的冷链物流配送成本自动核算方法

Automatic cost accounting method for cold chain logistics distribution based on spatial clustering algorithm

摘要

冷链配送由于其能最大程度保证运输产品的质量,但这也在无形中增加了冷链配送成本。因此精确核算配送成本以及最大程度控制成本成为冷链物流业亟待突破的难题。基于此,研究提出了将凝聚层次聚类方法与回归分析方法进行结合,以避免决策者主观因素对核算结果带来的影响,并在此基础上搭建出冷链物流配送成本自动核算模型。结果显示,研究所设计的核算模型对B22成本指标核算的准确率与实际成本最为接近。其中,核算准确率最大值与实际成本最大值差距为3.11%,最大差值出现在64.25万元时。上述结果证明,所提成本自动核算模型为冷链物流企业提供了一种客观、精准的成本核算与控制工具,有助于在保障运输质量的同时降低配送成本,推动低碳、低成本冷链物流的可持续发展。

Abstract

Cold chain distribution can maximize the quality of transported products, but this also invisibly increases the cost of cold chain distribution. Therefore, accurately calculating distribution costs and maximizing cost control become urgent challenges for the cold chain logistics industry to overcome. Based on this, the study proposes to combine the cohesive hierarchical clustering method with regression analysis method to avoid the influence of subjective factors of decision makers on the accounting results, and on this basis, a cold chain logistics distribution cost automatic accounting model is built. The results show that the accounting model designed by the research institute has the closest accuracy to the actual cost of B22 cost indicator accounting. Among them, the maximum difference between the accounting accuracy and the actual cost is 3.11%, with the maximum difference occurring at 642 500 yuan. The above results demonstrate that the proposed cost automatic accounting model provides an objective and accurate cost accounting and control tool for cold chain logistics enterprises, which helps to reduce distribution costs while ensuring transportation quality, and promotes the sustainable development of low-carbon and low-cost cold chain logistics.

关键词

聚类算法 / 成本核算 / AGNES / 回归分析

Key words

clustering algorithm / cost accounting / AGNES / regression analysis