Applying Probabilistic Model Checking to Express Delivery Location Selection and Optimization

Yonghua Zhu, Xiaoyi Xue, Kaiwen Zhang, Shunyi Mao, Honghao Gao
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引用次数: 4

Abstract

According to our survey about the express delivery from hundreds of campuses, we find that the location of commodity storage places impacts the delivery success rate and service quality. Thus, how to select the proper delivery location is vital to logistics enterprises, which contributes to improve the work efficiency and reduce delivery costs. In this paper, probabilistic model checking is used to verify the delivery fetch system, which evaluates the solution of location distributions in a quantitative way. First, it formalizes the fetch process of express delivery system between business and customer in the form of Discrete-Time Markov Chain (DTMC) when considering the stochastic behavior. Second, Probabilistic Computation Tree Logic (PCTL) is introduced as the verification property to the temporal behavior checking. Third, formal verifications are conducted by the supporting tool PRISM concerning on the transition probabilities computing. Furthermore, verification results are proven to follow the law of Bernouli Large Numbers, which aims to illustrate that the simulation result is close to the actual express delivery situation. Fourth, the express delivery location model is extended as new structure Co-DTMC in order to calculate time consumption and cost consumption, where the punishment factor is designed for the purpose of optimization. Finally, experiments are carried out to show that our approach can effectively select an optimal place for express delivery, which provides an alternative solution to integrate time and cost into the location selection.
概率模型检验在快递配送地点选择与优化中的应用
根据我们对数百个校园快递的调查,我们发现商品存放地点的位置影响着快递成功率和服务质量。因此,如何选择合适的配送地点对物流企业来说至关重要,这有助于提高工作效率,降低配送成本。本文采用概率模型检验方法对配送取货系统进行了验证,定量地评价了配送取货系统的位置分布解。首先,在考虑随机行为的情况下,以离散时间马尔可夫链(DTMC)的形式将快递系统中商家与顾客之间的取货过程形式化;其次,引入概率计算树逻辑(PCTL)作为时态行为检查的验证属性。第三,利用支撑工具PRISM对转移概率计算进行形式化验证。验证结果符合伯努利大数定律,说明仿真结果与快递实际情况较为接近。第四,将快递配送区位模型扩展为新结构Co-DTMC,计算时间消耗和成本消耗,并设计惩罚因子进行优化。最后,通过实验证明,该方法能够有效地选择出最优的快递投递地点,为快递投递地点的选择提供了一种将时间和成本结合起来的替代方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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