摘要
研究了多目标多阶段混合流水车间的紧急订单插单重调度问题,综合考虑工件批量、刀具换装时间、运输能力等约束.先以最小化订单完工时间和最小化总运输时间为双目标建立静态初始订单调度模型,再针对紧急订单插单干扰,增加最小化总加工机器偏差值目标,建立三目标重调度优化模型,并分别用NSGA-Ⅱ算法与融合基于事件驱动的重调度策略和重排插单策略的NSGA-Ⅲ算法对两个模型进行求解.最后,以某实际船用管类零件生产企业为案例,先对NSGA-Ⅱ算法和NSGA-Ⅲ算法的性能进行评估,得到NSGA-Ⅱ算法更适用于解决双目标优化问题而NSGA-Ⅲ算法在解决三目标优化问题时表现更优的结论,再将所建模型与所提算法应用于该企业的十组插单案例中,所得优化率接近三分之一,验证了实用性和有效性.
To study the multi-objective rush order insertion rescheduling problem under hybrid flow shop with multiple stages and multiple machines, the constraints, such as job lots, sequence-dependent set-up times, and round-trip transportation times, were simultaneously considered. A static optimal scheduling model of initial orders was first established to minimize the maximum order completion time and minimize the total transportation time. The non-dominated sorting genetic algorithm(NSGA)-Ⅱ algorithm was applied to solve a two-objective optimal problem. Then, for the rush order insertion disturbance factor, the objective to minimize the total machine deviation between the initial scheduling and rescheduling plans was added as a stability index to establish an optimal rush order rescheduling model. The NSGA-Ⅲ algorithm based on the event-driven rescheduling strategy and order rearrangement strategy was applied to solve a three-objective optimal problem. Finally, a realistic ship pipe parts manufacturing enterprise is regarded as a study case. Two sets of experiments are carried out to explain the motivation of the selected method. The performances of the NSGA-Ⅱ and NSGA-Ⅲ algorithms are evaluated by three metrics, including the mean ideal distance, spread of non-dominated solution, and percentage of domination. The results show that the NSGA-Ⅱ algorithm is more suitable for solving two-objective optimal problem,whereas NSGA-Ⅲ algorithm performs better in solving three-objective optimal problems. Then, the proposed model and method were applied to 10 rush order insertion cases of the enterprise. All the three objectives were improved according to the compared results obtained by the actual and optimal scheduling. The optimal rate is close to one third, which verifies the feasibility of the proposed model and the effectiveness of the proposed method.The proposed model and method may assist other enterprises that apply make-to-order production mode to reduce the impact of rush order insertion and realize a win-win mechanism between enterprises and customers.
作者
何小妹
董绍华
HE Xiao-me;DONG Shao-hua(School of Mechanical Engineering,University of Science and Technology Beijing,Beijing 100083,China)
出处
《工程科学学报》
EI
CSCD
北大核心
2019年第11期1450-1457,共8页
Chinese Journal of Engineering
基金
国家自然科学基金资助项目(71301008)
