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相关概念视频

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

48
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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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
640
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

107
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
107
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

456
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
456
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.5K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
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Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

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According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
130

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相关实验视频

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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一个灰狼优化算法用于多目标累积容量车辆路由问题,考虑到操作时间.

Gewen Huang1,2, Yuanhang Qi3, Yanguang Cai2

  • 1Information and Network Center, Jiaying University, Meizhou 514015, China.

Biomimetics (Basel, Switzerland)
|June 26, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了人道主义援助物流的新模式,优化车辆路线,最大限度地减少救灾等待时间和运营成本. 与现有方法相比,一种新的算法DGWO-F2OPT显著提高了效率和解决方案质量.

关键词:
累积容量车辆路线问题 累积容量车辆路线问题动态灰狼优化算法 动态灰狼优化算法应急物流的紧急物流漂浮的2-opt可以使用.这是一个多重目标的多重目标.

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科学领域:

  • 运营研究 运营研究
  • 物流和供应链管理的物流和供应链管理.
  • 灾害管理 灾害管理

背景情况:

  • 人道主义援助的交付面临的挑战是有效的车辆安排,以尽量减少接收者等待时间.
  • 传统的车辆路由模型往往忽略了诸如驾驶员工作量和现场决策需求等实际因素.
  • 通过运行时间和采用多目标建模来评估驾驶员的强度对于实际的援助物流至关重要.

研究的目的:

  • 引入一个双目标模型,考虑运行时间的多目标累积容量车辆路由问题 (MO-CCVRP-OT).
  • 尽量减少灾区累积等待时间,并减少因过度救援车辆运行时间造成的额外费用.
  • 开发一个高效的优化算法来解决MO-CCVRP-OT模型.

主要方法:

  • 提出了一个动态灰狼优化算法,具有浮动的2-opt (DGWO-F2OPT),集成实数编码,随机键解码和ROV规则.
  • 实施了动态非主导解决方案集更新策略,以提高算法性能.
  • 引入了多目标改进的浮动2-opt (F2OPT) 地方搜索,以实现高效的问题解决和更快的融合.

主要成果:

  • 与DGWO-F2OPT相比,DGWO-F2OPT在其乌托邦最佳解决方案的平均适应性值低6.22%.
  • 在比较试验中,DGWO-F2OPT的平均健康值比NS-2OPT低16.49%.
  • MO-CCVRP-OT模型显示,欧几里德距离与乌托邦点的距离比传统的CVRP-OT更接近18.72%.

结论:

  • 提议的DGWO-F2OPT算法有效地解决了MO-CCVRP-OT,平衡了人道主义援助交付速度和运营成本效率.
  • 新的算法在解决方案质量和融合速度方面明显优于现有方法.
  • MO-CCVRP-OT为人道主义物流提供了更全面的方法,考虑了关键的现实世界的操作约束.