基于混合鲸鱼算法的风电玻板生产智能排程
Intelligent Scheduling of Wind Power Glass Panel Production Based on Hybrid Whale Algorithm
杨欣 1杨晓英 2闫欢欢 3裴志杰4
作者信息
- 1. 河南科技大学,商学院,河南洛阳 471023;河南工学院管理学院,河南新乡 453000
- 2. 河南科技大学,商学院,河南洛阳 471023;河南科技大学,机电工程学院,河南洛阳 471023;机械装备先进制造河南省协同创新中心,河南洛阳 471003
- 3. 河南科技大学,机电工程学院,河南洛阳 471023
- 4. 河南科技大学,商学院,河南洛阳 471023
- 折叠
摘要
针对产品多级顺序齐套、异构并行机任务配置等复杂特征的风电玻板生产排程问题,考虑设备区域式分布、混胶工艺和换型准备等约束,建立以最大化设备利用率、最大化履约率、最大化同托卷工单顺序完工率等为指标的多目标优化模型,改进设计求解该排程模型的混合多目标鲸鱼优化算法.通过三段式编码方式将连续型鲸鱼算法离散化,引入精英策略以提升鲸鱼优化算法的收敛速度,并加入变邻域搜索算法,提高算法的全局搜索能力.通过仿真对比验证了算法的有效性,并基于制造执行系统进行实际应用,研究成果为风电玻板生产排程智能决策提供了有效的解决方法.
Abstract
Aiming at the production scheduling problems of wind power glass panel with complex characteristics such as multi-stage sequential assembly and heterogeneous parallel machine task configuration,considering the constraints of regional distribution of equipment,mixing process and transformation preparation,a multi-objective optimization model is established which takes maximization of equipment utilization rate,maximization of performance rate and maximization of sequential completion rate of the same roll work order as indicators.A hybrid multi-objective whale optimization algorithm is designed to solve the scheduling model.The continuous whale algorithm is discretized by three-stage coding,introducing elite strategy to improve the convergence speed of whale optimization algorithm.Finally,the variable neighborhood search algorithm is added to improve the global search ability of the algorithm.The effectiveness of the algorithm is verified by the simulation comparison.The practical application based on manufacturing execution system(MES)provides an effective solution for intelligent decision-making of wind power glass plate production schedule.
关键词
风电玻板/生产排程/多目标优化/鲸鱼算法Key words
wind power glass panel/production scheduling/multi-objective optimization/whale optimization algorithm引用本文复制引用
出版年
2024
NETL
NSTL
万方数据