基于改进鲸鱼算法的工业操作系统资源实例化调度算法研究
Research on Resource Instantiation Scheduling Algorithm for Industrial Operating Systems Based on Improved Whale Optimization Algorithm
潘志杰 1舒挺1
作者信息
- 1. 浙江理工大学计算机科学与技术学院,浙江 杭州 310018
- 折叠
摘要
工业操作系统借助资源实例化调度(RIS)技术管理制造资源时,会面临众多功能相似但服务质量各异的生产资源,导致资源选择和配置变得复杂.针对这一现状,提出了黄金柯西鲸鱼优化算法(GCWOA),该算法通过融合Tent混沌映射、黄金分割系数和柯西变异算子,实现对RIS问题的优化,提升服务质量.通过开展不同规模的RIS仿真实验验证,GCWOA展现出了显著的优势.相较于遗传算法、鲸鱼算法和2个改进鲸鱼算法,GCWOA的平均求解精度提升了5.6%,平均时间效率提高了2.35倍.以上结果充分证明了GCWOA在解决RIS问题上的高效性和实用性,为工业操作系统的资源管理提供了有力的优化工具.
Abstract
When managing manufacturing resources through Resource Instantiation Scheduling(RIS)technology,industrial operating systems face numerous production resources that are functionally similar but vary in service quality,leading to complex resource selection and configuration.To address this problem,a Golden Cauchy Whale Optimization Algorithm(GCWOA)is proposed to optimize the RIS problem and improve the service quality by combining the Tent chaotic mapping,the golden ratio and the Cauchy mutation operator.Validation through simulation experiments of various scales demonstrates that GCWOA exhibits significant advantages.Compared to genetic algorithms,traditional whale optimization algorithms,and two improved whale optimization algorithms,GCWOA achieves an average solution accuracy improvement of 5.6%and an average time efficiency increase of 2.35 times.These results strongly demonstrate the efficiency and practicality of GCWOA in solving RIS problems,providing a powerful optimization tool for resource management in industrial operating systems.
关键词
工业操作系统/资源调度/鲸鱼优化算法/元启发式算法Key words
industrial operating systems/resource scheduling/Whale Optimization Algorithm/metaheuristic algorithm引用本文复制引用
出版年
2025
NETL
NSTL
万方数据