【作者】 季子默； 李元特； 李林依； 李姝仪； 单子瑄； 乔非； 马玉敏； 王俊凯；

【Author】 Zimo Ji;Yuante Li;Linyi Li;Shuyi Li;Zixuan Shan;Fei Qiao;Yumin Ma;Junkai Wang;Tongji University, College of Electronics and Information Engineering;Tongji University, School of Economic Management;

【机构】 同济大学电子与信息工程学院； 同济大学经济与管理学院；

【摘要】 近年来受新冠疫情影响,国内外工厂都被迫出现停工、缓工的情况,对全球经济与社会造成了巨大冲击。面向人员多要素的柔性作业车间调度优化有助于提高生产效率,适应工作时间变动性,降低工人疲劳度,增强企业的抗风险能力。本文在设备资源约束的基础上,考虑工人因技能熟练度带来的工种的匹配度问题;同时,兼顾工人排班作息和请假休息,以最小化提前-拖期惩罚和工厂用工成本为目标,研究柔性作业车间问题特征下的多目标调度优化问题。通过构建相应数学模型,提出在改进NSGA-Ⅱ算法框架下的寻优策略,得到人员多因素作用下的双目标Pareto前沿及可行方案。此外,通过多目标算法的对比分析,实验结果表明本研究在应对双资源约束调度问题上可获得可靠且较优的解决方案。更多还原

【Abstract】 In recent years, affected by the new coronavirus epidemic, factories at home and abroad have been forced to implement shutdowns and delays, which has caused a huge impact on the global economy and society.Optimizing flexible job shop scheduling with multiple factors related to personnel can help improve production efficiency, adapt to changes in working hours, reduce worker fatigue, and enhance a company’s resilience to risks.This paper considers the issue of job matching based on workers’ skill proficiency in the context of equipment resource constraints. It also takes into account worker scheduling and their leave for rest, aiming to minimize lead time penalties and labor costs in the scheduling of flexible workshops, considering multiple objectives. By constructing a corresponding mathematical model and proposing an improved optimization strategy within the framework of the NSGA-II algorithm, the study obtains Pareto frontiers and feasible solutions for the dual objectives under the influence of various factors on personnel. Furthermore, through comparative analysis with other algorithms, experimental results demonstrate that this research provides reliable and relatively optimal solutions to address scheduling problems with dual resource constraints.更多还原