基于柯西游走的改进灰狼算法求解FJSP
An improved Gray Wolf algorithm based on Cauchy wander to solve FJSP
齐娅惠 1田云娜 1田园 1何雨欣 1韩小颖1
作者信息
- 1. 延安大学 数学与计算机科学学院,陕西 延安 716000
- 折叠
摘要
为了提高生产资源的利用率和调度效率,提出了一种基于柯西游走的灰狼优化算法,将其应用于求解柔性作业车间调度问题(FJSP).在经典灰狼算法的基础上,加入柯西游走策略跳出局部最优;引入非线性收敛因子a控制算法的广度搜索与深度搜索程度;采用混合生成新解的种群更新策略适当增强种群多样性.通过在不同规模的测试用例上进行仿真实验和分析比较,实验结果表明,基于柯西游走的灰狼算法寻优性能稳定,在平衡算法的全局搜索和局部搜索程度方面表现较为出色.
Abstract
To improve the utilization rate and scheduling efficiency of production resources,a grey Wolf optimiza-tion algorithm based on Cauchy wander was proposed and applied to flexible job-shop scheduling problems(FJSP).On the basis of the classical grey Wolf algorithm,Cauchy wandering strategy was added to escape the local optimal.The nonlinear convergence factor a was introduced to control the breadth search and depth search.The population diversity was appropriately enhanced by the population renewal strategy of hybrid generation of new solu-tions.Through simulation experiments and analysis on different scale test cases,the experimental results show that the Grey Wolf optimization based on Cauchy wander has stable optimization performance,and performs well in balancing the global search and local search degree of the algorithm.
关键词
灰狼优化算法/柯西分布/非线性收敛/柔性作业车间调度Key words
Gray Wolf optimization algorithm/Cauchy distribution/nonlinear convergence/flexible job shop scheduling引用本文复制引用
基金项目
国家自然科学基金(61763046)
国家自然科学基金(62041212)
国家级大学生创新创业训练计划(202210719041)
延安大学研究生教育创新计划(YCX2023007)
延安大学研究生教育创新计划(YCX2023004)
延安大学研究生教育创新计划(YCX2022071)
延安大学研究生教育创新计划(YCX2021053)
延安大学大学生创新创业训练计划创新训练项目(D2021147)
出版年
2024
NETL
NSTL
万方数据