在化学检查的异质机器人系统中进行任务分配的改进的艺术素算法
Chaofan Li1, Qiang Liu2, Mingqiang Yin1
1School of Information and Control Engineering, Liaoning Petrochemical University, Fushun, 113001, China.
Scientific reports
|December 1, 2025
概括
本研究介绍了一种增强的算法,用于在化学检查中将任务分配给多个异质机器人. 新方法提高了识别危险和降低生产风险的效率和稳定性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 运营研究 运营研究
背景情况:
- 对多个机器人进行高效的任务分配对于化学检查至关重要,以便及时检测危险并降低风险.
- 多重异质机器人任务分配 (MHRTA) 问题是复杂的,因为传感器适用性限制及其NP-hard性质.
研究的目的:
- 为MHRTA问题开发一个有效的整数编程模型.
- 提出一种新的,增强的算法,以有效地解决MHRTA模型.
主要方法:
- 考虑到传感器限制,为MHRTA建立了一个整数编程模型.
- 开发了一种多策略增强的艺术素算法,结合了粘液模具算法概念,非线性概率因子和自适应的t分布突变.
- 整合了双层编码方案和可变邻域搜索,以解决离散优化和提高计算效率.
主要成果:
- 拟议的算法在解决MHRTA问题方面表现出强大的优化能力和稳定性.
- 八个测试案例的实验结果验证了该方法的性能与其他算法和CPLEX解决方案相比.
结论:
- 增强的素算法为化学检查中复杂的MHRTA问题提供了强大的和高效的解决方案.
- 通过先进的机器人任务分配,开发的方法有助于提高工业化学环境中的安全性和效率.
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