莫斯斯:通过爱因斯坦的概念进行工程多目标优化
Vahid Goodarzimehr1, João Luiz Junho Pereira2, Nima Khodadadi3
1Faculty of Civil Engineering and Architecture, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
PloS one
|July 29, 2025
概括
介绍多目标特殊相对论搜索 (MOSRS),一个新的元启发算法. 对于复杂的问题,MOSRS有效地以最小的用户输入和较低的计算成本找到最佳的帕雷托前线 (PF).
科学领域:
- * 计算智能和数学优化.
- * 将物理原理应用于算法设计.
背景情况:
- *元启发学对于解决复杂的多目标优化问题至关重要.
- * 现有的算法通常需要广泛的参数调整,并与收和覆盖面作斗争.
- * 需要高效的算法,以降低计算成本提供优质的帕雷托前线 (PF).
研究的目的:
- * 引入新的多目标特殊相对论搜索 (MOSRS) 算法.
- * 证明MOSRS能够根据特殊相对论原理自适应参数的能力.
- * 评估MOSRS在具有挑战性的基准和现实世界问题上的表现,与已建立的元启发方法进行对比.
主要方法:
- * MOSRS算法的开发灵感来自特殊相对论物理学.
- * MOSRS应用于CEC 2009测试函数和21个现实世界受制的问题.
- *使用绩效指标进行比较分析:逆代距离,间距,最大传播和超量.
- *与11个最先进的元启发术 (NSGA-II,NSGA-III,MOEA/D,MOPSO,MOGWO,ARMOEA,TiGE2,CCMO,TOP,AND) 进行了比较.
主要成果:
- * MOSRS在大多数测试问题中在识别最佳帕雷托前线 (PF) 中表现出强的表现.
- * 该算法与其他11个元启发术相比,取得了竞争性或优异的结果.
- * MOSRS需要最小的用户干预,主要只需要代和粒子的数量.
结论:
- * MOSRS是一种高度有效和高效的元启发方法,用于多目标优化.
- *基于特殊相对论原理的算法的自适应参数调整有助于其性能.
- * MOSRS为研究人员和从业人员提供了一个有前途的替代方案,他们寻求复杂性降低的先进优化解决方案.
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