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相关概念视频

Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Binomial Probability Distribution01:15

Binomial Probability Distribution

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A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
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Probability Distributions01:32

Probability Distributions

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 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
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To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
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相关实验视频

Updated: May 15, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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一种基于抽样的获胜者确定模型和算法,用于在双重不确定性下进行物流服务采购拍卖.

Mingqiang Yin1, Hao Wang1, Qiang Liu2

  • 1School of Information and Control Engineering, Liaoning Petrochemical University, Fushun, 113001, Liaoning, China.

Scientific reports
|April 8, 2025
PubMed
概括

本研究为第四方物流平台开发了一种混合战略,以管理来自需求和干扰不确定性的风险. 拟议的模型和启发式算法有效地将成本降至最低,并优于现有的解决方案.

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科学领域:

  • 物流和供应链管理的物流和供应链管理.
  • 运营研究 运营研究
  • 风险管理 风险管理

背景情况:

  • 第四方物流平台 (4PL) 面临着来自需求和干扰不确定性的重大风险.
  • 传统的获胜者确定模型很难解释这些双重不确定性.
  • 有效的风险减轻策略对于4PL的运营效率至关重要.

研究的目的:

  • 在需求和颠覆不确定性下,为4PL平台开发一个强大的获胜者确定模型.
  • 提出一个混合风险减缓战略,整合临时外包和强化.
  • 为了最大限度地降低总运营成本,同时对抗已识别的风险.

主要方法:

  • 构建了一个两阶段的随机获胜者确定模型.
  • 将模型转换为混合整数线性编程问题,使用改进的样本平均近似 (SAA) 算法.
  • 开发了一个基于采样的启发式算法,结合了双分解,拉格朗的放松和场景减少.

主要成果:

  • 拟议的启发式算法在解决复杂情景时,与CPLEX相比,表现优越.
  • 数字示例和现实世界的案例验证了模型和算法的有效性.
  • 敏感性分析证实了需求波动和中断概率对策略选择的重大影响.

结论:

  • 混合缓解策略有效地对冲4PL获胜者确定中的双重不确定性.
  • 开发的SAA和启发式算法为复杂的随机优化问题提供了高效的解决方案.
  • 调查结果为4PL平台提供了优化风险管理和运营成本的宝贵见解.