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A differential evolutionary algorithm improvement framework based on artificial potential fields
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DOI：10.1016/j.asoc.2026.114714.png)
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摘要
En 中文
• Linked APF pathfinding principles to EA optimization processes. • Novel APF application enhances EA performance, targeting DE mutation. • Developed a mutation mechanism utilizing APF-derived attractive and repulsive forces. • Validated the framework’s effectiveness on varying real-world engineering problems.
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
机构
引用论文
Differential evolution algorithm with multi-population cooperation and multi-strategy integration
PREAI
分享收藏分享收藏Intelligent Intersection Control for Delay Optimization: Using Meta-Heuristic Search Algorithms.png)
SUSTAINABILITY
OAAI
SUSTAINABILITYIF3.3
OAAI分享收藏Differential evolution with multi-population based ensemble of mutation strategies基于多种群的变异策略集成的差分进化
PREAI
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