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相关概念视频

Conservation of Small Populations02:04

Conservation of Small Populations

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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
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Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
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混合塔布-灰狼优化算法用于增强新鲜的冷链物流分销.

Hao Zhang1, Jianing Yan1, Liling Wang1

  • 1School of Business, Beijing Technology and Business University, Beijing, China.

PloS one
|August 29, 2024
PubMed
概括

一个新的混合 Tabu-Grey wolf优化器 (TGWO) 算法优化了新鲜产品冷链物流,降低了成本并提高了效率. 这种方法可以在复杂的供应链中提高车辆排程和产品质量.

科学领域:

  • 运营研究 运营研究
  • 供应链管理 供应链管理
  • 人工智能的人工智能

背景情况:

  • 越来越多的新鲜产品需求需要高效的冷链物流.
  • 目前的系统面临着温度控制和交货延迟等挑战,导致产品损失和成本增加.
  • 优化对于保持产品质量和降低新鲜产品分销的运营成本至关重要.

研究的目的:

  • 为优化新鲜产品冷链物流分销引入一种新型混合Taboo-Grey wolf优化器 (TGWO) 算法.
  • 为了最大限度地降低总分销成本,并在各种约束下建立高效的车辆调度方案.
  • 为了提高冷链物流优化的效率和解决方案质量.

主要方法:

  • 开发了一种混合的 Tabu-Grey wolf优化器 (TGWO) 算法,将 Tabu Search (TS) 结合用于探索和 Grey Wolf Optimizer (GWO) 结合用于开发.
  • 实施TGWO以优化车辆调度并最大限度地降低冷链物流中的分销成本.
  • 实验验证和对粒子集群优化 (PSO),鱼优化算法 (WOA) 和原始GWO进行比较分析.

主要成果:

  • 与PSO,WOA和GWO相比,TGWO算法在优化冷链物流方面表现出更高的效率和解决方案质量.
  • 实验和案例研究验证了拟议的混合方法的有效性.

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  • TGWO成功地将分销成本降至最低,并改进了车辆调度计划.

    • 结论:

    • 像TGWO这样的混合优化技术在复杂的供应链网络和动态市场中是有效的.
    • 实施TGWO可以显著提高分销效率,降低成本,并保持冷链物流中的产品质量.
    • 未来的研究应该探索新的搜索运营商和各种现实场景,以提高TGWO的适用性.