摘要
为提升轴承盖柔性生产车间的调度效率,构建了一个以最小化最大完工时间、最大机器负荷及总机器负荷为目标的多目标调度优化模型。针对该问题,提出融合北方苍鹰策略的改进型麻雀搜索算法(northern harrier multi-Ob-jective sparrow search algorithm, NHMSSA)。算法引入Bernoulli混沌映射提升初始种群多样性,采用北方苍鹰勘探机制增强搜索能力,并结合自适应t分布变异与非支配排序方法,优化算法的全局寻优与局部收敛性能。通过ZDT与DTLZ系列测试函数的仿真试验,NHMSSA在解的精度、分布均匀性和收敛速度等方面均优于多目标粒子群、灰狼优化及NSGA-Ⅱ等典型算法。在标准算例及实际轴承盖制造车间数据集上的应用表明,所提算法可有效获得调度目标之间的均衡解集,展现出良好的实用性与稳定性。研究结果验证了NHMSSA在多目标柔性作业车间调度中的有效性和优越性,为复杂制造系统的调度优化问题提供了理论支撑与算法依据。
In this article,in order to improve the efficiency in flexible production shop scheduling of bearing caps,efforts are made to construct a multi-objective scheduling optimization model with the objective of minimizing the maximum completion time,the maximum machine load and the total machine load.To address this problem,an improved sparrow search algorithm(NHMSSA)incorporating the northern hawk strategy is proposed.The algorithm introduces Bernoulli chaotic mapping to enhance the initial population diversity,adopts the Northern Hawk exploration mechanism to improve the search capability,and combines adaptive t-distribution variation with the non-dominated sorting method to optimize the algorithm’s global search and local conver-gence performance.Through some simulation experiments on the ZDT and DTLZ series test functions,NHMSSA outperforms typi-cal algorithms such as multi-objective particle swarm,gray wolf optimization and NSGA-Ⅱin terms of solution accuracy,distribu-tion uniformity and convergence speed.The applications on standard arithmetic cases and actual bearing cap manufacturing work-shop datasets show that this algorithm can be used to effectively obtain a balanced solution set between scheduling objectives,with a high standard of practicality and stability.The results verify that NHMSSA is effective and superior in multi-objective flexible production shop scheduling.This study provides theoretical support and algorithmic basis for scheduling optimization of complex manufacturing systems.
作者
牛莉霞
毛振辉
NIU Lixia;MAO Zhenhui(School of Business Administration,University of Liaoning Technical,Huludao 125105)
出处
《机械设计》
北大核心
2025年第9期94-103,共10页
Journal of Machine Design
基金
国家自然科学基金项目(52174184)
河南省住房和城乡建设厅软科学研究项目(R-2318)。
关键词
柔性车间调度
轴承盖
多目标优化
麻雀搜索算法
flexible shop scheduling
bearing cap
multi-objective optimization
sparrow search algorithm
