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篮球团队优化算法 (BTOA):一个新的体育灵感的元启发式优化器,用于工程应用程序
Yujie Chen1, Guangyu Wang2, Baichuan Yin3
1School of Statistics, Dongbei University of Finance and Economics, Dalian, Liaoning, China.
Scientific reports
|July 2, 2025
概括
新的篮球团队优化算法 (BTOA) 通过使用体育激发的策略,有效地解决复杂,高维的优化问题. 这种新的元启发方法证明了对现实世界工程挑战的卓越性能和可靠性.
科学领域:
- 计算智能是一种计算智能.
- 优化算法 优化算法
- 超听证学是一种超听证学.
背景情况:
- 现实世界的优化问题越来越高维度,非线性和受约束,挑战现有的元启发术.
- 主流以人口为基础的方法在复杂的场景中经常遭受过早的融合和不良的勘探-开发平衡.
- 没有免费午餐定理需要针对不同问题类的域特定优化器.
研究的目的:
- 引入一项新的体育灵感元,篮球队优化算法 (BTOA),以解决现有优化技术的局限性.
- 通过可扩展模块来增强全球勘探和管理个体多样性,以实现更广泛的应用.
- 为了验证BTOA在基准函数和复杂的现实世界工程优化任务上的有效性.
主要方法:
- 开发了篮球团队优化算法 (BTOA),通过将篮球概念 (训练,快速休息,定位,传球) 映射到合作搜索操作员.
- 引入了两个可扩展的模块:用于增强全球勘探的动态定位策略和用于多样性管理的可变属性模块.
- 在多个维度 (30,50,100) 中对CEC2005和CEC2017基准套件进行了广泛的实验,并评估了无人机路径规划方面的表现.
主要成果:
- 在经过测试的维度中,BTOA在82.61%的CEC2005函数和绝大多数CEC2017函数上实现了最低的平均误差.
- 统计测试 (Wilcoxon signed-rank,Friedman) 证实了BTOA在其他算法上的性能增长的重要性.
- 对于具有复杂约束和大决策空间的现实问题,比如无人机路径规划,BTOA表现出强的表现.
结论:
- 拟议的篮球队优化算法 (BTOA) 为当代工程优化任务提供了可扩展和可靠的解决方案.
- BTOA有效地缓解了现有的元启发术的关键缺陷,特别是在处理高维,非线性和受约束问题的方面.
- 可扩展模块增强了启发式设计空间,可以集成到其他基于人口的优化器中.
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