Are the queueing systems in practice random or uncertain? Evidence from online car-hailing data in Beijing

IF 4.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Fuzzy Optimization and Decision Making Pub Date : 2024-09-05 DOI:10.1007/s10700-024-09430-0
Yang Liu, Zhongfeng Qin, Xiang Li
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Abstract

In order to rationally characterize the nondeterministic phenomena in queueing systems, there exist two mathematical systems, one is probability theory concerned with the analysis of random phenomena and the other is uncertainty theory concerned with the analysis of uncertain phenomena. Before using the above two mathematical systems to model the real queueing systems, we often need to face such a question, are the real queueing systems random or uncertain? In order to answer this question, we collect the arriving times of passengers from online car-hailing platform in Beijing, and then analyze the collected data based on stochastic renewal process and uncertain renewal process. Finally, by comparing samples and confidence intervals of the total numbers of passengers arriving on the online car-hailing platform under two mathematical systems, we come to the conclusion that the queueing systems in the real world are uncertain rather than random.

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实践中的排队系统是随机的还是不确定的?来自北京网约车数据的证据
为了合理地描述排队系统中的非确定现象,存在两个数学体系,一个是关注随机现象分析的概率论,另一个是关注不确定现象分析的不确定性理论。在使用上述两个数学体系对实际排队系统建模之前,我们往往需要面对这样一个问题:实际排队系统是随机的还是不确定的?为了回答这个问题,我们收集了北京网约车平台乘客的到达时间,然后基于随机更新过程和不确定更新过程对收集到的数据进行分析。最后,通过比较两种数学体系下网约车平台乘客到达总数的样本和置信区间,我们得出结论:现实世界中的排队系统是不确定的,而不是随机的。
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来源期刊
Fuzzy Optimization and Decision Making
Fuzzy Optimization and Decision Making 工程技术-计算机:人工智能
CiteScore
11.50
自引率
10.60%
发文量
27
审稿时长
6 months
期刊介绍: The key objective of Fuzzy Optimization and Decision Making is to promote research and the development of fuzzy technology and soft-computing methodologies to enhance our ability to address complicated optimization and decision making problems involving non-probabilitic uncertainty. The journal will cover all aspects of employing fuzzy technologies to see optimal solutions and assist in making the best possible decisions. It will provide a global forum for advancing the state-of-the-art theory and practice of fuzzy optimization and decision making in the presence of uncertainty. Any theoretical, empirical, and experimental work related to fuzzy modeling and associated mathematics, solution methods, and systems is welcome. The goal is to help foster the understanding, development, and practice of fuzzy technologies for solving economic, engineering, management, and societal problems. The journal will provide a forum for authors and readers in the fields of business, economics, engineering, mathematics, management science, operations research, and systems.
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