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摘要

Abstract


研究背景:越来越多的消费者更喜欢网上购物,购买更多的产品,企业正在争夺新技术和物流模式。

研究问题:CS在快递包裹配送中的应用,并设想了一种几乎不对组织负责人施加管理控制的具体CS模型。

研究方法:动态规划,比较法

研究结论:CS模型重点研究如何解决服务点之间转移的特定CS方法的可行性,本文提出了几种新的算法方法来解决CS网络实时管理中需要解决的实时包裹路由问题网络设计和管理问题为未来研究提供了新的研究方向。

Research background: More and more consumers prefer online shopping and purchase more products. Enterprises are competing for new technologies and logistics models.

Research question: the application of CS in express parcel delivery, and conceive a concrete CS model that almost does not impose management control on the person in charge of the organization.

Research method: dynamic programming, comparative method

Research conclusion: CS model focuses on the feasibility of specific CS methods to solve the transfer between service points. This paper proposes several new algorithms to solve the real-time package routing problem that needs to be solved in real-time management of CS network. Network design and management issues provide a new research direction for future research.


知识卡片

Knowledge card


Logistic回归模型


逻辑分布(Logistic distribution)公式:

P(Y=1 X=x)=exp(x'β)/(1+exp(x'β))

其中参数β常用极大似然估计。


可用于处理分类因变量的统计分析,克服了线性回归模型要求因变量是定量变量而不能是定性变量的局限性,多应用于社会科学。

特点:Logit模型因变量不是常规的连续变量,而是对数发生比率,尽管每个自变量的估计系数含义与一般线性回归一样,数的经济学含义,较方便的做法是将Logit进行转换后再进行解释,而不是直接解释系数本身,即将回归模型等式两侧取自然指数。


Logistic regression model


Logical distribution formula:

P(Y=1 X=x)=exp(x' β)/ (1+exp(x' β))

Where parameter β Maximum likelihood estimation is commonly used.


It can be used for statistical analysis of categorical dependent variables, overcoming the limitation of linear regression model that the dependent variables are quantitative variables rather than qualitative variables, and is mostly used in social science.

Features: The dependent variable of the Logit model is not a conventional continuous variable, but a logarithmic occurrence rate. Although the meaning of the estimated coefficient of each independent variable is the same as that of the general linear regression, the economic meaning of the number is more convenient to interpret after the Logit is converted, rather than directly explain the coefficient itself, that is, take the natural index on both sides of the equation of the regression model.


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参考资料:百度翻译、百度百科

[1]Barış Yıldız. Express package routing problem with occasional couriers[J]. Transportation Research Part C: Emerging Technologies, 2021, 123: 102994.


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页面更新:2024-05-04

标签:因变量   自变量   线性   系数   变量   包裹   路径   实时   含义   模型   快递   本文

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