具有学习效应的半导体晶圆制造绿色车间调度问题研究

doi:10.12005/orms.2021.0134

运筹与管理 ›› 2021, Vol. 30 ›› Issue (4): 217-223.DOI: 10.12005/orms.2021.0134

具有学习效应的半导体晶圆制造绿色车间调度问题研究

董君^1,2, 叶春明¹

1.上海理工大学管理学院,上海 200093;
2.河南工学院,河南新乡 453000

收稿日期:2019-04-17 出版日期:2021-04-25
作者简介:董君(1985-),女,河南焦作人,博士研究生,研究方向:智能算法,生产调度等;叶春明(1964-),男,安徽宣城人,教授,博士生导师,研究方向:工业工程、生产调度等。
基金资助:
国家自然科学基金资助项目(71840003);上海理工大学科技发展资助项目(2018KJFZ043)

Research on Green Job Shop Scheduling Problem of Semiconductor Wafers Manufacturing with Learning Effect

DONG Jun^1,2, YE Chun-ming¹

1. Business School, University of Shanghai for Science & Technology, Shanghai 200093, China;
2. Henan Institute of Technology, Xinxiang 453000, China

Received:2019-04-17 Online:2021-04-25

摘要/Abstract

摘要： 针对最小化最大完工时间、总碳排放以及总拖期时间的具有学习效应的半导体晶圆制造绿色车间调度问题,构建了双影响因素的新型学习效应模型,提出了改进的多元宇宙优化算法,并对其收敛性进行证明。通过对初始种群进行反向学习、宇宙个体进行莱维飞行扰动和对外部档案中的个体进行邻域搜索变异更新,产生新的父代个体,扩大了种群的多样性,避免算法陷入局部最优。通过对小规模和大规模测试算例的仿真实验,以及利用改进算法求解具有异质性机器的学习型半导体晶圆制造绿色车间调度问题,验证了本文所提出的算法对于求解具有学习效应的半导体晶圆制造绿色车间调度问题的有效性和可行性。

关键词: 学习效应, 异质性机器, 半导体晶圆制造, 绿色调度

Abstract: In order to minimize makespan, total carbon emissions and total tardiness, we construct a new learning effect model with double influencing factors firstly. Thus an improved Multi-Verse Optimizer algorithm is proposed and its convergence is also proved. By performing reverse learning on the initial population, perturbing the individuals in the universe population by Levy flight, and mutating and updating the individuals in the external archive by neighborhood search, new parent individuals are generated, which expand the diversity of the population and avoid the algorithm falling into local optimum. Through the simulation experiments of small-scale and large-scale test cases, and the use of improved algorithm to solve the green shop scheduling problem of learning semiconductor wafers fabrication with heterogeneous machines, it is verified that the proposed algorithm for solving the green shop scheduling problem of semiconductor wafers fabrication with learning effect is valid and feasible.

Key words: learning effect, heterogeneous machines, semiconductor wafers manufacturing, green scheduling

中图分类号:

TP18

董君, 叶春明. 具有学习效应的半导体晶圆制造绿色车间调度问题研究[J]. 运筹与管理, 2021, 30(4): 217-223.

DONG Jun, YE Chun-ming. Research on Green Job Shop Scheduling Problem of Semiconductor Wafers Manufacturing with Learning Effect[J]. Operations Research and Management Science, 2021, 30(4): 217-223.

参考文献

[1] 江志斌.半导体芯片制造系统建模与优化调度控制[M].上海交通大学出版社,2011.
[2] 姚远远,叶春明,杨枫.双目标可重入混合流水车间调度问题的离散灰狼优化算法[J].运筹与管理,2019,28(8):190-199.
[3] Ying K C,Lin S W,Wan S Y.Bi-objective reentrant hybrid flowshop scheduling: an iterated pareto greedy algorithm[J].International Journal of Production Research,2014,52(19): 5735-5747.
[4] Shen J N,Wang L,Zheng H Y.A modified teaching-learning-based optimisa-tion algorithm for bi-objective re-entrant hybrid flowshop scheduling[J].International Journal of Production Research,2016,54(12): 3622-3639.
[5] Shen J N,Wang L,Deng J,Zheng X L.A pareto-based discrete harmony search algorithm for bi-objective reentrant hybrid flowshop scheduling problem[C].//Proceedings of the 2nd International Conference on Harmony Search Algorithm (ICHSA2015).Berlin: Springer,2016: 435-445.
[6] 轩华,李冰,罗书敏,王薛苑.基于总加权完成时间的可重入混合流水车间调度问题[J].控制与决策,2018,33(12):2218-2226.
[7] 中国工程院战略咨询中心.绿色制造[M].北京:电子工业出版社,2016:1-6.
[8] Ding J Y,Song S J,Wu C.Carbon-efficient scheduling of flow shops by multi-objective optimization[J].European Journal of Operational Research,2016,248(3): 758-771.
[9] Liu Q,Chekem F O,Zhan M M,Shao X Y,Ying B S,Sutherland J W.A hybrid fruit fly algorithm for solving flexible job-shop scheduling to reduce manufacturing carbon footprint[J].Journal of Cleaner Production,2017,168: 668-678.
[10] Piroozfard H,Wong K Y,Wong W P.Minimizing total carbon footprint and total late work criterion in flexible job shop scheduling by using an improved multi-objective genetic algorithm[J].Resources,Conservation and Recycling,2018,128: 267-283.
[11] 侯丰龙,叶春明,耿秀丽.基于多目标萤火虫膜算法的学习效应生产调度问题[J].系统管理学报,2018,27(4):107-114.
[12] Ji M,Tang X Y,Zhang X,Cheng T C E.Machine scheduling with deteriorating jobs and deJong's learning effect[J].Computers &Industrial Engineering,2016,91: 42-47.
[13] Toksari M D,Arik O A.Single machine scheduling problems under position-dependent fuzzy learning effect with fuzzy processing times[J].Journal of Manufacturing Systems,2017,45: 159-179.
[14] 刘琼,梅侦.面向低碳的工艺规划与车间调度集成优化[J].机械工程学报,2017,53(11):164-174.
[15] Mirjalili S,Mirjalili S M,Hatamlou A.Multi-verse optimizer: a nature-inspired algorithm for global optimization[J].Neural Computing and Applications,2015,27(2): 495-513.
[16] Deb K,Pratap A,Agarwal S,Meyarivan T.A fast and elitist multiobjective genetic algorithm NSGA-II[J].IEEE Transaction on Evolutionary Computation,2002,6(2): 182-197.
[17] Cho H M,Bae S J,Kim J,Jeong I J.Bi-objective scheduling for reentrant hybrid flow shop using pareto genetic algorithm[J].Computers and Industrial Engineering,2011,61(3): 529-541.
[18] Dong J,Ye C M.Research on collaborative optimization of green manufacturing in semiconductor wafer distributed heterogeneous factory[J].APPL SCI-BASEL.2019,9(14),2879.

具有学习效应的半导体晶圆制造绿色车间调度问题研究

Research on Green Job Shop Scheduling Problem of Semiconductor Wafers Manufacturing with Learning Effect

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 11

编辑推荐

Metrics

[1]	孙丽, 马卫民. 带恶化和综合学习效应的成组排序问题研究[J]. 运筹与管理, 2020, 29(3): 125-127.
[2]	叶春明, 侯丰龙, 赵静. 具有学习-遗忘效应的半导体批调度问题研究[J]. 运筹与管理, 2019, 28(7): 192-199.
[3]	刘春来, 王建军. 具有学习和退化效应的单机干扰管理问题[J]. 运筹与管理, 2019, 28(1): 94-100.
[4]	郭苗苗, 刘桓, 王吉波, 牛玉萍. 具有学习效应和加工时间可控的平行机排序问题[J]. 运筹与管理, 2018, 27(3): 113-117.
[5]	周意元, 张强, 王利明, 陈纲. 具有学习效应的排序对策[J]. 运筹与管理, 2018, 27(1): 49-52.
[6]	余英, 程明宝. 带学习效应和资源依赖的单机排序模型[J]. 运筹与管理, 2018, 27(1): 53-58.
[7]	闫萍, 王吉波, 赵礼强. 带准备时间的单机指数时间学习效应排序问题[J]. 运筹与管理, 2017, 26(11): 70-76.
[8]	马卫民, 孙丽. 在成组技术下带恶化和学习效应的单机排序问题[J]. 运筹与管理, 2017, 26(1): 25-28.
[9]	陈俊霖, 赵晓波, 宋亚楠, 陈建铭. 一类供应链中考虑公平关切的学习效应行为实验研究[J]. 运筹与管理, 2015, 24(2): 20-28.
[10]	于秀丽, 张毕西, 李逸帆, 李弘. 考虑员工学习效应的MTO/MOS指派模型及算法研究[J]. 运筹与管理, 2014, 23(1): 226-233.
[11]	张新功, 严广乐, 唐国春, 唐海波. 具有指数和位置学习效应的机器排序问题[J]. 运筹与管理, 2011, 20(2): 97-101.