Please wait a minute...
浙江大学学报(工学版)
自动化技术     
需求与公用工程不确定的生产计划与调度集成
王越, 苏宏业, 邵寒山, 卢山,谢磊
浙江大学 智能系统与控制研究所,浙江 杭州 310027
Integration of production planning and scheduling under demand and utility uncertainties
WANG Yue, SU Hong ye, SHAO Han shan, LU Shan, XIE Lei
Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, China
 全文: PDF(1424 KB)   HTML
摘要:

为了降低生产过程中的不确定因素对生产计划和调度的影响,考虑需求和公用工程的不确定性,建立多周期计划和调度双层集成模型.根据时间尺度的不同,分别在计划层和调度层处理需求和公用工程的不确定性.在计划层,引入机会约束随机规划来描述需求不确定性,基于离散时间建模方法建立离散时间线性不确定模型,考虑了生产率波动和参考库存约束.在调度层,引入模糊理论来表示公用工程的不确定性,基于特定单元事件点的连续时间建模方法建立关于多阶段多用途的间歇过程连续时间混合整数线性不确定模型.利用滚动优化策略对计划和调度双层模型进行迭代求解.通过经典算例验证了该模型的可行性和有效性.采用该方法有效地降低了两种不确定参数对优化结果的影响,提高了设备和公用工程的利用率.

Abstract:

 A multi-period bi-level integrated planning and scheduling model was formulated by considering demand and utility uncertainties in order to reduce the effects of uncertain factors in production process on production planning and scheduling. Demand and utility uncertainties were dealt with separately in planning and scheduling layers according to the difference of time scale. In planning layer, chance constraint stochastic programming was introduced to describe the demand uncertainty. An uncertain discrete-time linear programming model was formulated based on discrete-time modeling method. The fluctuations of production rate and deviations from the reference limits of inventory were considered. In scheduling layer, the fuzzy theory was utilized to describe the utility uncertainty. An uncertain continuous-time mixed-integer linear programming model related to multistage multipurpose batch process was formulated based on unit-specific event-based continuous-time modeling method. The bi-level planning and scheduling models were iteratively solved by rolling horizon optimization strategy. The feasibility and effectiveness of the proposed model was illustrated through a benchmark example from literatures. The proposed method can effectively reduce the effects of the two uncertainties and increase the utilization of equipments and utilities.

出版日期: 2017-01-01
CLC:  TH 166  
基金资助:

国家“863”高技术研究发展计划资助项目(2014AA041803);国家自然科学基金资助项目(61134007).

通讯作者: 苏宏业,男,教授. ORCID: 0000-0002-7003-1000.     E-mail: hysu@iipc.zju.edu.cn
作者简介: 王越(1985—),女,博士生,从事不确定条件下生产计划和调度的建模与优化研究.ORCID:0000-0001-7726-5267. E-mail:yuewang@zju.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章  

引用本文:

王越, 苏宏业, 邵寒山, 卢山,谢磊. 需求与公用工程不确定的生产计划与调度集成[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2017.01.007.

WANG Yue, SU Hong ye, SHAO Han shan, LU Shan, XIE Lei. Integration of production planning and scheduling under demand and utility uncertainties. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2017.01.007.

[1] WANG W, LI X, GAO L, et al. Application of interval theory and genetic algorithm for uncertain integrated process planning and scheduling [C]∥ 2013 IEEE International Conference of Systems, Man, and Cybernetics (SMC). Manchester: IEEE, 2013: 2796-2801.
[2] CHU Y F, YOU F Q, WASSICK J M, et al. Integrated planning and scheduling under production uncertainties: bilevel model formulation and hybrid solution method [J]. Computers and Chemical Engineering, 2015, 72: 255-272.
[3] MULA J, POLER R, GARCIASABATER J P, et al. Models for production planning under uncertainty: areview  [J]. International Journal of Production Economics, 2006, 103(1): 271-285.
[4] CHAKRABORTTY R K, HASIN M A A, SARKER R A, et al. A possibilistic environment based particle swarm optimization for aggregate production planning [J]. Computers and Industrial Engineering, 2015,88: 366-377.
[5] ANDRE L, ROUSSOS D. Stochastic optimization of mine production scheduling with uncertain ore/metal/waste supply [J]. International Journal of Mining Science and Technology, 2014, 24(6): 755-762.
[6] XU B, ZHONG P A, ZAMBON R C, et al. Scenario tree reduction in stochastic programming with recourse for hydropower operations [J]. Water ResourcesResearch, 2015, 51(8): 6359-6380.
[7] IRIS C, CEVIKCAN E. A fuzzy linear programming approach for aggregate production planning [M]. Berlin: Springer, 2014: 355-374.
[8] YANG H B, MAO F Y, XU J H, et al. Parallel machine scheduling with fuzzy due date using improved simulated annealing in lean production [C] ∥ Applied Mechanics and Materials. Shenzhen: Trans Tech Publications, 2014, 457: 470-473.
[9] DONYA R, REZA R, PARVIZ F, et al. A robust optimization model for multiproduct twostage capacitated production planning under uncertainty [J]. Applied Mathematical Modeling, 2013, 37(20): 8957-8971.
[10] 田野,董宏光,邹雄,等.考虑需求不确定性的化工生产计划与调度集成[J].化工学报,2014, 65(09): 3552-3558.
TIAN Ye, DONG Hongguang, ZOU Xiong, et al. Chemical production planning and scheduling integration under demand uncertainty [J]. CIESC Journal, 2014, 65(09): 3552-3558.
[11] WANG Y, SU H Y, SHAO H S, et al. Hierarchical approach of planning and scheduling with demand uncertainty and utility disturbance [C]∥The 5th International Symposium on Advanced Control of Industrial Process. Hiroshima, Japan: [s. n.], 2014: 28-30.
[12] 于春云,赵希男,彭艳东,等.模糊随机需求模式下的扩展报童模型与求解算法[J].系统工程,2006, 24(9): 103-107.
YU Chunyun, ZHAO Xinan, PENG Yandong, et al. Extended Newsboy problem based on fuzzy random demand [J]. Systems Engineering, 2006, 24(9):103-107.
[13] MARAVELIAS C T, GROSSMANN I E. New general continuoustime statetask network formulation for shortterm scheduling of multipurpose batch plants [J]. Industrial and Engineering Chemistry Research, 2003, 42(13): 3056-3074.
[14] WANG Y, SU H Y, SHAO H S, et al. Unitspecific eventbased and slotbased hybrid model framework with hierarchical structure for shortterm scheduling [J]. Mathematical Problems in Engineering, 2015, 501: 906-280

[1] 周爱民,刘宏斌,张书涛,欧阳晋焱. 面向汽车主客观审美评价的不确定性推理模型[J]. 浙江大学学报(工学版), 2021, 55(3): 419-429.
[2] 周爱民,周彩霞,欧阳晋焱,张书涛. 基于指标适度标准化的界面风格美综合评价模型[J]. 浙江大学学报(工学版), 2020, 54(12): 2273-2285.
[3] 罗仕鉴, 董烨楠. 面向创意设计的器物知识分类研究[J]. 浙江大学学报(工学版), 2017, 51(1): 113-123.
[4] 文贤鹤, 周晓军, 杨辰龙. 云制造模式车辆试验服务平台构建方法[J]. 浙江大学学报(工学版), 2016, 50(12): 2254-2261.
[5] 刘征宏, 谢庆生, 李少波, 林丽. 基于潜在语义分析和感性工学的用户需求匹配[J]. 浙江大学学报(工学版), 2016, 50(2): 224-233.
[6] 董辉跃,朱灵盛, 章明, 李少波,罗水均. 飞机蒙皮切边的螺旋铣削方法[J]. 浙江大学学报(工学版), 2015, 49(11): 2033-2039.
[7] 朱上上,罗仕鉴. 产品设计中基于设计符号学的文物元素再造[J]. J4, 2013, 47(11): 2065-2070.
[8] 伍晓榕,裘乐淼,张树有,孙良峰,郭传龙. 模糊语境下的复杂系统关联FMEA方法[J]. J4, 2013, 47(5): 782-789.
[9] 萨日娜, 张树有. 复杂产品设计方案联合变权群决策方法[J]. J4, 2013, 47(4): 711-719.
[10] 张卫,潘晓弘,王正肖,田景红,吴鹏程. 基于信息熵免疫优化的制造服务开发策略[J]. J4, 2011, 45(11): 1908-1912.
[11] 邱清盈, 张惠, 冯培恩. 专利知识辅助产品创新的方法[J]. J4, 2011, 45(2): 228-233.
[12] 白翱, 唐任仲, 王志国, 等. 离散制造业射频识别技术导入的多层决策模型[J]. J4, 2009, 43(12): 2196-2202.
[13] 刘江, 陈芨熙, 顾新建, 等. 技术路线图导向的知识网络模型[J]. J4, 2009, 43(12): 2218-2224.
[14] 徐河杭, 顾新建, 祁国宁, 等. 企业协同专利分析平台[J]. J4, 2009, 43(10): 1853-1857.