arrival distribution

简明释义

到达分布

英英释义

例句

1.The logistics team analyzed the arrival distribution 到达分布 of shipments to optimize warehouse space.

物流团队分析了货物的到达分布 arrival distribution以优化仓库空间。

2.Understanding the arrival distribution 到达分布 of customers can help improve service efficiency.

了解顾客的到达分布 arrival distribution可以帮助提高服务效率。

3.The airport's flight schedule is designed around the arrival distribution 到达分布 of incoming flights.

机场的航班安排是围绕到达航班的到达分布 arrival distribution设计的。

4.The restaurant modified its staffing based on the expected arrival distribution 到达分布 of diners during peak hours.

餐厅根据高峰时段预期的到达分布 arrival distribution调整了员工配置。

5.We used statistical models to predict the arrival distribution 到达分布 of calls at the call center.

我们使用统计模型预测呼叫中心的到达分布 arrival distribution。

作文

In the field of operations research and queueing theory, the concept of arrival distribution plays a crucial role in understanding how entities arrive at a service point. The arrival distribution refers to the statistical description of the time intervals between consecutive arrivals in a system. This concept is particularly important in various industries such as telecommunications, transportation, and service management, where managing the flow of incoming requests or customers is essential for efficiency and effectiveness.To illustrate the significance of arrival distribution, consider a busy coffee shop located in a bustling city. During peak hours, customers arrive at random intervals, and the management needs to understand these patterns to optimize service delivery. By analyzing the arrival distribution of customers, the coffee shop can determine the average arrival rate and identify peak times when additional staff may be required. This analysis helps in minimizing wait times and enhancing customer satisfaction.There are several types of arrival distributions that can be observed in different scenarios. One common model is the Poisson distribution, which is often used to describe random arrivals over a fixed period. In this model, the number of arrivals in a given time frame follows a predictable pattern, allowing businesses to forecast demand accurately. For instance, if the coffee shop notices that on average, ten customers arrive every fifteen minutes, they can use this information to ensure that there are enough baristas available during those times.Another type of arrival distribution is the exponential distribution, which describes the time between successive arrivals. This distribution is particularly useful for modeling scenarios where events occur continuously and independently. For example, if a taxi service wants to analyze how frequently passengers request rides, they can apply the exponential distribution to understand the average waiting time between ride requests. By doing so, they can allocate their resources effectively to meet demand without overstaffing.Understanding arrival distribution is not just about predicting customer behavior; it also informs decision-making processes in resource allocation and operational efficiency. For instance, hospitals often experience fluctuating patient arrivals in the emergency department. By studying the arrival distribution of patients, healthcare administrators can implement strategies to ensure that sufficient medical staff and resources are available during high-demand periods. This proactive approach can significantly improve patient care and reduce overcrowding.Moreover, the insights gained from analyzing arrival distribution can lead to better forecasting models that incorporate seasonality and trends. Businesses can leverage historical data to refine their understanding of customer behavior, leading to more accurate predictions of future demand. This knowledge empowers organizations to make informed decisions regarding staffing, inventory management, and service capacity.In conclusion, the concept of arrival distribution is integral to optimizing operations across various sectors. By comprehensively understanding how and when entities arrive, businesses can enhance their service delivery, improve customer satisfaction, and ultimately drive success. Whether in a coffee shop, a transportation service, or a healthcare facility, the analysis of arrival distribution provides valuable insights that contribute to effective management and operational excellence.

在运筹学和排队理论领域，到达分布的概念在理解实体如何到达服务点方面起着至关重要的作用。到达分布指的是连续到达之间时间间隔的统计描述。这个概念在电信、交通运输和服务管理等各个行业中都尤为重要，因为管理进来的请求或客户流对于效率和有效性至关重要。为了说明到达分布的重要性，考虑一下位于繁忙城市中的一家咖啡店。在高峰时段，顾客以随机间隔到达，管理层需要了解这些模式，以优化服务交付。通过分析顾客的到达分布，咖啡店可以确定平均到达率，并识别出需要额外员工的高峰时段。这种分析有助于最小化等待时间并提升顾客满意度。在不同场景中，可以观察到几种类型的到达分布。一种常见模型是泊松分布，它通常用于描述固定时间内的随机到达。在这个模型中，给定时间框架内的到达数量遵循可预测的模式，使企业能够准确预测需求。例如，如果咖啡店注意到平均每十五分钟有十名顾客到达，他们可以利用这些信息确保在这些时段有足够的咖啡师可用。另一种到达分布是指数分布，它描述了连续到达之间的时间。这种分布在建模事件持续且独立发生的场景时特别有用。例如，如果一家出租车服务想要分析乘客请求乘车的频率，他们可以应用指数分布来了解请求之间的平均等待时间。通过这样做，他们可以有效分配资源，以满足需求而不至于人手过多。理解到达分布不仅仅是预测客户行为；它还为资源分配和运营效率的决策过程提供了信息。例如，医院在急诊科经常会经历患者到达的波动。通过研究患者的到达分布，医疗管理者可以实施策略，以确保在高需求期间有足够的医务人员和资源可用。这种主动的方法可以显著改善患者护理并减少拥挤。此外，从分析到达分布中获得的洞察可以导致更好的预测模型，这些模型融合了季节性和趋势。企业可以利用历史数据来细化对客户行为的理解，从而更准确地预测未来的需求。这种知识使组织能够就员工配置、库存管理和服务能力做出明智的决策。总之，到达分布的概念对于优化各个行业的运营至关重要。通过全面理解实体如何以及何时到达，企业可以提升服务交付，提高客户满意度，并最终推动成功。无论是在咖啡店、交通服务还是医疗设施中，对到达分布的分析提供了宝贵的洞察，促进了有效的管理和卓越的运营。