由埃尔多斯-雷尼复杂网络指导的进化算法
Víctor A Bucheli1, Oswaldo Solarte Pabón1, Hugo Ordoñez2
1Escuela de Ingeniería de Sistemas y Computación, Universidad del Valle, Cali, Valle, Colombia.
PeerJ. Computer science
|January 23, 2024
概括
本研究介绍了一种使用埃尔多斯 - 雷尼复杂网络的新型进化算法,以改善旅行销售员问题 (TSP) 等优化问题的解决方案精细化. 网络引导的方法展示了卓越的性能,更快的融合和更短的执行时间.
科学领域:
- 计算智能是一种计算智能.
- 网络科学 网络科学
- 优化算法 优化算法
背景情况:
- 进化算法 (EAs) 被广泛用于复杂的优化问题.
- 传统的EAs在解决方案的精细化和融合速度方面可能面临挑战.
- 复杂的网络提供了一个框架来建模人口内部的关系和动态.
研究的目的:
- 提出一种新的进化算法,集成埃尔多斯-雷尼复杂网络.
- 加强对人口交叉和候选解决方案改进的监管.
- 调查网络结构对优化性能的影响.
主要方法:
- 将算法的群体概念化为一个相互关联的复杂网络.
- 使用埃尔多斯-雷尼随机图来建模解决方案之间的动态连接.
- 将拟议的算法与传统的EA和其他基于网络的算法进行比较.
主要成果:
- 埃尔多斯-雷尼的动态网络引导算法超过了传统和替代的基于网络的算法.
- 拟议的模型实现了更好的收率.
- 通过新方法观察到更短的执行时间.
结论:
- 复杂的网络特征为解决优化问题提供了宝贵的见解.
- 网络结构可以有效地调节优化决策过程.
- 埃尔多斯-雷尼网络的拟议整合为增强进化计算提供了一个有希望的策略.
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