一个改进的白生命周期优化算法,用于全球功能优化
1School of Electrical Engineering, Northeast Electric Power University, Jilin, Jilin, China.
PeerJ. Computer science
|March 10, 2025
概括
一个改进的白生命周期优化算法 (ITLCO) 提高了融合速度和准确性. 对于工人和士兵的新型战略,再加上一个替代机制,平衡人口多样性,并防止局部优化,以获得更好的优化性能.
科学领域:
- 计算智能是一种计算智能.
- 优化算法 优化算法
- 群集情报 群集情报 群集情报
背景情况:
- 超启发式算法对于解决复杂的优化问题至关重要.
- 虫生命周期优化算法 (TLCO) 是一种由虫行为启发的生物算法.
- 现有的TLCO版本在平衡融合速度和人口多样性方面面临挑战,冒着当地最佳的风险.
研究的目的:
- 引入一个改进的白生命周期优化算法 (ITLCO).
- 为了提高TLCO算法的趋同速度和准确性.
- 解决平衡人口多样性和趋同的局限性,以避免局部最佳.
主要方法:
- 制定了一项新的员工培养战略,以改善沟通和平衡融合/多样性.
- 引入了一种带有进化步骤因子的士兵生成策略,以提高趋同速度.
- 为维持人口多样性,实施了低质量个体的替代更新机制.
主要成果:
- 伊特尔科在CEC2013,CEC2019和CEC2020基准测试功能上表现出色.
- 改进后的算法显示了对汇率速度和准确度的显著增长.
- 与基本的TLCO和其他四个领先的元启发算法相比,ITLCO表现出增强的稳定性.
结论:
- 拟议的ITLCO有效地改进了原来的TLCO算法.
- ITLCO提供了融合和多样性之间的更好的平衡,减轻了局部最佳的风险.
- 增强的策略有助于更快,更准确,更稳定的优化结果.
更多相关视频
11:53The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
11.5K
11:53Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
12.9K
相关概念视频
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
38
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...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
38
01:29Life Histories
17.7K
Overview
17.7K