摘要
针对多品种、小批量、强交货期的柔性生产方式下云制造智能车间机床资源再分配服务问题,以各工件在机床上加工的最短完成时间、机器总负荷最小、成本最低为多目标函数,以机床均衡率为综合评判函数,建立了再分配服务模型。采用一种基于Pareto外部档案的多目标教与学优化算法对上述模型进行了求解,仿真结果表明多目标教与学优化算法在收敛性和求解效率等方面具有较大优势。研究可为解决云制造平台下的智能车间生产规划难题提供有益指导。
Aiming at the problem of machine tool redistribution service with multi-variety small-batch and short delivery time characteristics in a cloud manufacturing-based workshop,the objective function was defined as the shortest completion time,the least total load and the lowest cost of each workpiece.Based on the comprehensive evaluation function of the machine tool equilibrium rate,a redistribution service model was established.The above model was solved by a multi-objective teaching and learning based optimization algorithm based on Pareto external archives.The simulation results show that the multi-objective teaching and learning optimization algorithm has great advantages in convergence and efficiency.Useful guidance can be provided for solving the production planning problem of smart workshop under cloud manufacturing platform.
作者
张富强
李植新
张金源
ZHANG Fu-qiang;LI Zhi-xin;ZHANG Jin-yuan(Key Laboratory of Road Construction Technology and Equipment of MOE, Chang’an University, Xi’an 710064, China;Institute of Smart Manufacturing Systems Engineering, Chang’an University, Xi’an 710064, China)
出处
《科学技术与工程》
北大核心
2020年第22期8983-8988,共6页
Science Technology and Engineering
基金
国家自然科学基金(51605041)
中央高校基本科研业务费专项资金基础研究项目(300102258112)
陕西省科技重大专项(2018zdzx01-01-01)。
关键词
云制造
智能车间
再分配服务
多目标教与学优化算法
cloud manufacturing
smart workshop
redistribution service
multi-objective teaching and learning based optimization algorithm
