摘要
针对再制造系统多种不确定因素,包括回收质量、准备时间、加工时间等,研究面向再制造系统的批量调度问题。考虑回收产品存在质量差异的情况,将回收品划分为几种质量不同的工件组类型,各工件组内所有工件的准备时间和加工时间相同,为了减小准备时间和子系统切换时间,将同一工件组内的工件分批量进行调度处理。在满足交货期、加工次序和机器有限等约束条件下,以加权完工时间最小化为目标,建立了模糊环境下的混合整数规划调度模型。该问题包含了工件分批次和调度顺序两个子问题,使用遗传算法进行求解,结合实际算例得出调度策略,验证了该模型在处理再制造生产调度问题上的有效性,并进一步分析了不同批量大小对再制造调度结果的影响。
Considering the unique characteristics of uncertainty including ready time, subsystem switch time, process time in the remanufacturing system, we analyze the scheduling problem with job family for remanufacture. In the paper, independent waste work-pieces are grouped into multiple classes based on similarity in quality, so that the ready time and the processing time of the works in the same class are equal. Then the jobs from the same class are partitioned into batches to reduce the ready time and the subsystem switch time. Under the constraint of the delivery date, the processing sequence and the limited machine, we established a mixed integer programming scheduling model, trying to minimum the completion time. The problems include the batch sub-problem and the scheduling sub-problem,and we use GA to solve it. The performance of the model was evaluated through simulation, so that we can prove its effectiveness and try to analysis how the batch size affects the scheduling results.
出处
《工业工程与管理》
CSSCI
北大核心
2012年第6期34-40,46,共8页
Industrial Engineering and Management
基金
国家自然科学基金资助项目(70971022)
国家自然科学基金资助项目(71271054)
国家自然科学基金青年项目(71102164)
教育部人文社会科学研究青年基金项目(10YJC630249)
关键词
再制造
模糊不确定性
批量调度
遗传算法
remanufacturing
fuzzy uncertainty
batch scheduling
Genetic Algorithm
