新改进的混合遗传算法用于优化可重新配置制造系统的设施布局设计
Xiaoxiao Wei1, Jiafan Sun1, Haojin Jiao2
1School of Modern Post, Xi 'an University of Posts and Telecommunications, Xi 'an, 710061, China.
Scientific reports
|July 2, 2025
概括
一个新的混合基因算法改进了可重新配置制造系统的设备布局设计. 这种方法提高了复杂的NP难题的准确性和效率.
科学领域:
- 工业工程 工业工程 工业工程
- 运营研究 运营研究
- 计算机科学 计算机科学
背景情况:
- 在可重新配置的制造系统中,设备布局设计是一个复杂的,NP难题.
- 现有的算法与这些系统日益增长的维度和复杂性作斗争.
研究的目的:
- 提出一个新的,改进的混合基因算法,以优化设备布局设计.
- 为了提高解决NP-hard布局设计问题的效率和准确性.
主要方法:
- 使用混沌基因算法与改进的帐地图进行初始人口增强.
- 应用关联规则理论来识别主导区块和结合人工染色体.
- 包括匹配的交叉,突变操作和适应性混乱扰动.
主要成果:
- 拟议的混合遗传算法与传统方法相比,表现优越.
- 实验结果显示,在准确性和效率方面都有显著的改进.
结论:
- 开发的算法有效地解决了可重新配置制造系统布局设计的复杂性.
- 这种方法为制造业的NP-hard优化问题提供了更准确,更有效的解决方案.
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