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Mixed integer programming models for concurrent configuration design and scheduling in a reconfigurable manufacturing system
Concurrent Engineering Pub Date : 2020-01-22 , DOI: 10.1177/1063293x19898727
Jianping Dou 1 , Chun Su 1 , Xia Zhao 2
Affiliation  

A reconfigurable manufacturing system can evolve its configuration to offer exactly the capacity and functionality needed for every demand period. For the reconfigurable manufacturing system with multi-part flow-line configuration simultaneously producing multiple parts within the same family, the production cost and the delivery time are closely related to its configuration and corresponding scheduling for certain demand period. Although studies on multi-part flow-line configuration design are abundant, studies on concurrent optimization of configuration design and scheduling for reconfigurable manufacturing system are scarce. First, a generic mixed integer nonlinear programming model for concurrent configuration design and scheduling is established to relax the limitation of the existing model, and then a mixed integer linear programming model is derived. The decisions of the two generalized models are to decide the amount of stations, the amount of identical machines and machines’ configuration for every station, and assign parts to machines along the multi-part flow line together with sequencing assigned parts for each machine. Based on the mixed integer linear programming model, an exact ε-constraint method is developed to obtain the Pareto optimal solutions with tradeoffs between cost and tardiness. The validation of two models and the ε-constraint method is verified against two cases adapted from the literature.

中文翻译:

用于可重构制造系统中并发配置设计和调度的混合整数规划模型

可重构制造系统可以改进其配置,以准确提供每个需求周期所需的容量和功能。对于具有多零件流线配置的可重构制造系统,在同一族内同时生产多个零件,其生产成本和交货时间与其配置和特定需求周期的相应调度密切相关。尽管对多部分流线配置设计的研究很多,但对可重构制造系统的配置设计和调度并行优化的研究却很少。首先,建立了一个通用的混合整数非线性规划并发配置设计和调度模型,以放松现有模型的局限性,进而推导出混合整数线性规划模型。两个广义模型的决策是确定工位数量、相同机器的数量和每个工位的机器配置,并沿着多部件流线将部件分配给机器,并为每台机器排序分配的部件。在混合整数线性规划模型的基础上,开发了一种精确的ε约束方法,以在成本和延迟之间进行权衡来获得帕累托最优解。两个模型和 ε 约束方法的验证针对从文献改编的两个案例进行了验证。并沿着多部件流线将部件分配给机器,并为每台机器分配分配的部件。在混合整数线性规划模型的基础上,开发了一种精确的ε约束方法,以在成本和延迟之间进行权衡来获得帕累托最优解。两个模型和 ε 约束方法的验证针对从文献改编的两个案例进行了验证。并沿着多部件流线将部件分配给机器,并为每台机器分配分配的部件。在混合整数线性规划模型的基础上,开发了一种精确的ε约束方法,以在成本和延迟之间进行权衡来获得帕累托最优解。两个模型和 ε 约束方法的验证针对从文献改编的两个案例进行了验证。
更新日期:2020-01-22
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