云制造平台下订单可分解的协同生产计划模型及求解
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摘要
针对云平台下多订单在多企业多时段的协同生产计划问题,引入订单拆分数和订单最小分解率这两个调节变量,在考虑生产时间窗和生产能力等约束下建立协同生产计划模型.同时,设计双层编码,并运用自适应模拟退火遗传算法在不同数据规模下对模型进行求解,求解结果与商用优化软件CPLEX进行比较.最后对模型中的关键参数进行了灵敏度分析,实验结果为云制造平台运营决策者提供决策依据.
In cloud manufacturing platform,a multi-plants and multi-periods collaborative production problem was discussed by introducing two adjustive variables,which are the maximal number of enterprises that process an order and the minimal order splitting ratio,respectively.We established a collaborative production planning model with constrains of production time window and production capacity.Then,a self-adaptive simulated annealing genetic algorithm using bi-level code was designed.Our proposed approach was compared with a commercial optimization software CPLEX under different data sizes in numerical simulation.Lastly,the sensitivity analysis of the major parameters in the model was carried on.The experimental results provide a decision-making basis for operation decision makers of cloud manufacturing platform.
In cloud manufacturing platform,a multi-plants and multi-periods collaborative production problem was discussed by introducing two adjustive variables,which are the maximal number of enterprises that process an order and the minimal order splitting ratio,respectively.We established a collaborative production planning model with constrains of production time window and production capacity.Then,a self-adaptive simulated annealing genetic algorithm using bi-level code was designed.Our proposed approach was compared with a commercial optimization software CPLEX under different data sizes in numerical simulation.Lastly,the sensitivity analysis of the major parameters in the model was carried on.The experimental results provide a decision-making basis for operation decision makers of cloud manufacturing platform.
引文
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[11] BRAHIMI N,DAUZERE-PERES S,WOLSEY L A.Polyhedral and Lagrangian approaches for lot sizing with production time windows and setup times[J].Computers&Operations Research,2010,37(1):182-188.
[2] CAO Y,WANG S L,KANG L,et al.A TQCSbased service selection and scheduling strategy in cloud manufacturing[J].International Journal of Advanced Manufacturing Technology,2016,82:235-251.
[3] ZHANG M,LI C Q,SHANG Y L,et al.Research on resource service matching in cloud manufacturing[J].Manufacturing Letters,2018,15:50-54.
[4] FISHER O,WATSON N,PORCU L,et al.Cloud manufacturing as a sustainable process manufacturing route[J].Journal of Manufacturing Systems,2018,47:53-68.
[5]周金宏,汪定伟.软计算求解分布式多工厂单件制造业的提前/拖期生产计划问题[J].控制理论与应用,2002,19(2):235-238.ZHOU Jinhong,WANG Dingwei.Soft computing for earliness and tardiness production planning of multi-location OKP manufacturing systems[J].Control Theory&Applications,2002,19(2):235-238.
[6] KARIMI N,DAVOUDPOUR H. A branch and bound method for solving multi-factory supply chain scheduling with batch delivery[J].Expert Systems with Applications,2015,42:238-245.
[7]王文浩,张洁.面向ATP的多工厂订单决策与生产计划集成优化模型[J].上海交通大学学报,2011,45(12):1794-1799.WANG Wenhao,ZHANG Jie.An order decision and production planning integrated available-to-promise model for multi-plant manufacturing[J].Journal of Shanghai Jiao Tong University,2011,45(12):1794-1799.
[8] PAN T Y,ZHANG Z H,CAO H.Collaborative production planning with production time windows and order splitting in make-to-order manufacturing[J].Computer&Industrial Engineering,2014,67:1-9.
[9] LU Y Q,XU X.Process and production planning in a cloud manufacturing environment[C]∥Proceedings of the ASME 2015International Manufacturing Science and EngineeringConference. Charlotte, USA:MSEC,2015:9382.
[10]王占中,赵利英,曹宁博.基于多层编码遗传算法的危险品运输调度模型[J].吉林大学学报(工学版),2017,47(3):751-755.WANG Zhanzhong,ZHAO Liying,CAO Ningbo,et al. Hazardous material transportation scheduling model based on multilayer coding genetic algorithm[J].Journal of Jilin University(Engineering and Technology Edition),2017,47(3):751-755.
[11] BRAHIMI N,DAUZERE-PERES S,WOLSEY L A.Polyhedral and Lagrangian approaches for lot sizing with production time windows and setup times[J].Computers&Operations Research,2010,37(1):182-188.