摘要
针对车间的调度问题,现有研究多集中于生产效率的单一优化,忽略了机器负载、能耗等方面的优化。为提高作业车间的生产效率,同时优化车间内多个核心指标,建立了包含最小化最大加工时间、机械负载、以及加工能耗等指标的车间调度模型。提出了混合交叉搜索策略的灰狼算法(MSS-GWO),通过引入选择系数提高了种群的多样性;并设计了一种非线性函数进行动态调整全局搜索和局部搜索以保持种群多样性的同时使算法快速收敛;对领导狼引入动态权重避免算法陷入局部最优解。通过MK数据集测试,验证了混合交叉搜索策略的有效性,并与其他文献的方法进行对比,验证了算法在多目标车间调度问题的优越性。
In terms of the scheduling issue of the workshop, current research focuses on the single optimization of production efficiency, ignoring the optimization of machine load and energy consumption.In order to improve the production efficiency of the workshop and optimize multiple core indicators in the workshop, a workshop scheduling model with indicators such as minimized maximum processing time, mechanical load and processing energy consumption was established.The MSS-GWO of hybrid cross-search strategy is proposed, which improves the diversity of the population by introducing the selection coefficient and a nonlinear function is designed to dynamically adjust the global search and local search to maintain the diversity of the population while making the algorithm converge rapidly;the introduction of dynamic weights to the leading wolf avoids the algorithm falling into the local optimal solution.Through the MK dataset test, the effectiveness of the hybrid cross-search strategy is verified, and the superiority of the algorithm in the multi-target workshop scheduling problem is verified by comparing with the methods of other literature.
作者
冯麟皓
方喜峰
李俊
FENG Lin-hao;FANG Xi-Feng;LI Jun(School of Mechanical Engineering,Jiangsu University of Science and Technology,Zhenjiang 212100,China;Jiangsu Key Laboratory of Advanced Manufacturing Technology,Huaian 223003,China)
出处
《组合机床与自动化加工技术》
北大核心
2023年第1期168-172,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国防基础科研基金项目(A0720133010)
江苏省先进制造技术重点实验室开放基金资助(HGAMTL-1905)
镇江市重点研发计划项目(GY2019003,GY2020007)
江苏省研究生创新计划项目(KYCX22-3785)。
关键词
车间调度
灰狼算法
动态权重
非支配解集
workshop scheduling
grey wolf algorithm
dynamic weights
non-dominated solution
