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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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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.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Statically Indeterminate Problem Solving01:16

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Appropriate sampling methods ensure 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.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
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Machines: Problem Solving II01:30

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Most altruistic behavior—in which one animal helps another at a cost to themselves—occurs between relatives. Scientists think these altruistic behaviors evolved because they increase the inclusive fitness of the animal providing help.
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Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees
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一个人工蜂群优化算法,用于解决模糊容量后勤配送中心问题.

Yasser M Ayid1, Mohammad Zakaraia2, Mohamed Meselhy Eltoukhy3

  • 1Mathematics Department, Faculty of Sciences and Arts, Al-Kamil University of Jeddah, Saudi Arabia.

MethodsX
|October 9, 2024
PubMed
概括

本研究介绍了一种模糊模型,用于在不确定的工厂需求下优化配送中心选择. 它介绍了混合的人工蜜蜂群算法和基准问题,以提高物流规划和决策.

关键词:
一个人工蜂群优化算法,用于解决模糊容量物流配送中心问题.人工蜂群优化 蜂群优化有能力的物流配送中心.设计实验的设计.模糊的集合 模糊的集合

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科学领域:

  • 运营研究 运营研究
  • 物流管理物流管理
  • 模糊的集合理论 模糊的集合理论

背景情况:

  • 有能力的物流配送中心问题涉及选择最佳的配送中心以满足工厂的需求.
  • 现有的模型经常与不确定的需求作斗争,需要对现实世界的应用进行强大的方法.
  • 模糊逻辑提供了一个框架,用于模拟和管理需求预测和网络设计中的不确定性.

研究的目的:

  • 开发一种方法论方法来解决模糊容量物流配送中心问题.
  • 根据固定成本,容量和模糊工厂需求,优化分销中心的选择.
  • 提供一个基准数据集和先进的算法,用于研究和在物流分销实际应用.

主要方法:

  • 模糊需求通过将模糊需求转换为清晰的价值来解决模糊容量后勤配送中心问题的数学公式.
  • 三种不同的人工蜂群算法变体的混合化,采用启发式方法.
  • 应用Taguchi的直角数组来系统地优化算法参数.

主要成果:

  • 为在不确定的需求下选择配送中心而开发了一个模糊模型.
  • 创建了20个基准问题,以促进研究和比较分析.
  • 混合人工蜂群算法在解决问题的复杂性方面表现出有效性.

结论:

  • 提出的方法方法有效地解决了模糊容量后勤配送中心的问题.
  • 开发的算法和基准问题有助于推进不确定的物流规划研究.
  • 该研究提供了一个全面的工具包,用于优化不确定需求的配送中心选择.