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相关概念视频

The Availability Heuristic01:08

The Availability Heuristic

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A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
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Heuristics01:21

Heuristics

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Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
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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.
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

Statically Indeterminate Problem Solving

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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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Probability Histograms01:17

Probability Histograms

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A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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相关实验视频

Updated: May 7, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

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用知识的再利用和改进的启发式来解决垃圾堆问题的一种新方法.

Jie Fang1,2,3, Xubing Chen4,5, Yunqing Rao6

  • 1Hubei Provincial Key Laboratory of Chemical Equipment Intensification and Intrinsic Safety, Wuhan Institute of Technology, Wuhan, 430205, P. R. China.

Scientific reports
|December 31, 2024
PubMed
概括

本研究引入了针对二维不规则包装问题的新算法,提高了知识的再利用效率. KRIH算法提供了强大的解决方案,并且与现有方法具有竞争力.

关键词:
启发式算法 启发式算法不规则的部分不规则的部分知识的再利用知识的再利用.知识转移知识转移.包装问题 包装问题

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科学领域:

  • 运营研究 运营研究
  • 计算机科学 计算机科学
  • 人工智能的人工智能

背景情况:

  • 二维 (2D) 不规则包装问题是NP完整的,影响着服装和金属制造等行业.
  • 现有的混合启发式和元启发式算法复杂且耗时.

研究的目的:

  • 为2D不规则包装开发一个高效和强大的算法.
  • 从类似的包装任务中利用知识重复使用.
  • 为了改进经典的包装算法.

主要方法:

  • 利用双胞胎神经网络来测量包装任务之间的相似性.
  • 实施了知识再利用的转移运营商.
  • 改进了左下方的碎片放置算法.
  • 开发了知识再利用和改进启发式 (KRIH) 算法.

主要成果:

  • 在计算实验中,KRIH算法表现出良好的稳定性.
  • 在16个实例中,KRIH比经典算法取得了同等或更好的结果.
  • 该算法在相对较短的时间内运行.

结论:

  • 该KRIH算法有效地重复使用包装知识,提高效率.
  • 拟议的方法显示了对二维不规则包装问题的重大应用潜力.
  • 克里希为现有的包装解决方案提供了有竞争力的替代方案.