非线性工时多工艺路线条件下作业车间调度问题研究
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摘要
随着各种相关技术日趋成熟,车间制造装备的柔性能力得到了很大提高。在生产实践中,企业作业车间存在着非线性工序工时、功能组加工效率不确定、同一工件具有多工艺路线等问题。而在上述条件下的作业调度算法设计与求解也是需要解决的工程问题。本课题的研究针对上述工程问题,就非线性工时多工艺路线条件下的作业车间调度问题展开研究。
首先针对作业车间中功能组工序工时无法确定这一问题,提出了基于网络特征参数分析的功能组非线性工时研究方法,并建立了功能组的网络特征参数与功能组加工效率之间的关系模型。通过该模型,能够较好地预测功能组的非线性工时曲线。结论显示,适度的网络密度和网络接近中心度有利于提高功能组的加工效率,而网络密度和网络接近中心度太高或太低都不利于提高功能组的加工效率。
然后,针对作业车间中工件存在多工艺路线这一现象,以及传统的工艺建模存在的形式化问题,提出并建立了基于多色集合理论的多工艺路线析取方法。该方法能很方便地对复杂的零件加工系统进行表述建模,并且具有表达清晰、实现便捷的优点；同时,设计并介绍了基于模糊评判和基于遗传算法的多工艺路线优化决策的两种方法；通过对析取出的多加工路径进行优先级排序,提高了工艺设计的柔性程度,为车间调度提供柔性化的加工路径方案。
接着针对作业车间调度问题这一NP-hard优化难题,建立了多工艺路线条件下作业车间工件的加工时间搭接网络模型,为车间运行优化建模提供了新的思路和方法；同时,针对调度结果的设备负载不均衡的情况,将Wardrom用户平衡(UE)原理引入生产网络,建立了基于UE的任务均衡分配模型,并在此基础上,设计了一个新颖的算法——基于UE的改进遗传算法求解非线性工时多工艺路线条件下的作业车间调度问题,并通过几个实例,验证了该算法的有效性和新颖性。
最后,以某航天制造企业为研究实例,选取了一个具有非线性工时和多工艺路线的作业计划作为研究对象,对所取得的理论和方法成果进行了验证。
Along with the correlative with manufacturing technology has mature, the flexibility of machines has been improved greatly in job-shop. In practice, there are some problems in job-shop such as non-linear process time, uncertain process efficiency of function groups (FG), multi-process plans (MPP) and multi-process routes (MPR), Optimal decision problem of multi-process plans, and how to design the algorithms of job-shop scheduling problems (JSP) under the problems mentioned above. Just about these, the researches are valuable and challenging for solving the job-shop scheduling problems with non-linear process time and multi-process plans. Aimed at the engineering problems mentioned above, the research has been gone along as following.
Firstly, this research aims to the uncertain process efficiency of function groups (FG), a method has been proposed for forecasting the process efficiency of function groups using network characteristic analysis. By analyzing the relationship model between the network characteristic parameters and the process efficiency of function group, the results has been founded. That is that appropriate network density and network closeness centrality has positive contribution to FG performance, either too high or too low, restricts FG performance. To enhance FG productivity and achieve optimal performance, it is necessary to develop the tie relations (TR) among members, and the network should be moderate network density and keep appropriate distribution.
Secondly, there are multi-process plans in job-shop, and exiting the formalization problem modeling the process plan using conventional method, so extracting the process routes based on polychromatic set is presented. Its key idea is to use standardized mathematical model to simulate different objects. Due to the availability of the standardized mathematical model, polychromatic theory has made significant progress in problem formalization. Next, the methods based on fuzzy sets (FS) and genetic algorithm (GA) has been introdued separately using to range the priority of the process routes extracted using the methods based on fuzzy sets and genetic algorithm (GA). The program improved the flexibility of process plans, and provided optional process plan for job-shop scheduling.
Next, aims to job-shop scheduling problem, a process time pace network model has been constructed under multi-process plans, it provided a particular idea for modeling the job-shop scheduling. For the lopsided load of machines, load balancing model of process routes is established based on Wardrom User Equilibrium (UE) principle, and a improved genetic algorithm is designed based on UE for solving the JSP with non-linear process time and multi-process plans, and the effectiveness of the algorithm designed has been validated by comparing with other algorithms and other commercial software.
At last, according to a spaceflight manufacturing enterprise, and select a process task with non-linear process time and multi-process rotues as case study, by applying the achievement of this research, the effectiveness of this algorithm designed has been validated by comparing with other algorithms and other commercial software. Finally, a softeware tools of manufacturing executive system (MES) has been inrodued simply.
首先针对作业车间中功能组工序工时无法确定这一问题,提出了基于网络特征参数分析的功能组非线性工时研究方法,并建立了功能组的网络特征参数与功能组加工效率之间的关系模型。通过该模型,能够较好地预测功能组的非线性工时曲线。结论显示,适度的网络密度和网络接近中心度有利于提高功能组的加工效率,而网络密度和网络接近中心度太高或太低都不利于提高功能组的加工效率。
然后,针对作业车间中工件存在多工艺路线这一现象,以及传统的工艺建模存在的形式化问题,提出并建立了基于多色集合理论的多工艺路线析取方法。该方法能很方便地对复杂的零件加工系统进行表述建模,并且具有表达清晰、实现便捷的优点；同时,设计并介绍了基于模糊评判和基于遗传算法的多工艺路线优化决策的两种方法；通过对析取出的多加工路径进行优先级排序,提高了工艺设计的柔性程度,为车间调度提供柔性化的加工路径方案。
接着针对作业车间调度问题这一NP-hard优化难题,建立了多工艺路线条件下作业车间工件的加工时间搭接网络模型,为车间运行优化建模提供了新的思路和方法；同时,针对调度结果的设备负载不均衡的情况,将Wardrom用户平衡(UE)原理引入生产网络,建立了基于UE的任务均衡分配模型,并在此基础上,设计了一个新颖的算法——基于UE的改进遗传算法求解非线性工时多工艺路线条件下的作业车间调度问题,并通过几个实例,验证了该算法的有效性和新颖性。
最后,以某航天制造企业为研究实例,选取了一个具有非线性工时和多工艺路线的作业计划作为研究对象,对所取得的理论和方法成果进行了验证。
Along with the correlative with manufacturing technology has mature, the flexibility of machines has been improved greatly in job-shop. In practice, there are some problems in job-shop such as non-linear process time, uncertain process efficiency of function groups (FG), multi-process plans (MPP) and multi-process routes (MPR), Optimal decision problem of multi-process plans, and how to design the algorithms of job-shop scheduling problems (JSP) under the problems mentioned above. Just about these, the researches are valuable and challenging for solving the job-shop scheduling problems with non-linear process time and multi-process plans. Aimed at the engineering problems mentioned above, the research has been gone along as following.
Firstly, this research aims to the uncertain process efficiency of function groups (FG), a method has been proposed for forecasting the process efficiency of function groups using network characteristic analysis. By analyzing the relationship model between the network characteristic parameters and the process efficiency of function group, the results has been founded. That is that appropriate network density and network closeness centrality has positive contribution to FG performance, either too high or too low, restricts FG performance. To enhance FG productivity and achieve optimal performance, it is necessary to develop the tie relations (TR) among members, and the network should be moderate network density and keep appropriate distribution.
Secondly, there are multi-process plans in job-shop, and exiting the formalization problem modeling the process plan using conventional method, so extracting the process routes based on polychromatic set is presented. Its key idea is to use standardized mathematical model to simulate different objects. Due to the availability of the standardized mathematical model, polychromatic theory has made significant progress in problem formalization. Next, the methods based on fuzzy sets (FS) and genetic algorithm (GA) has been introdued separately using to range the priority of the process routes extracted using the methods based on fuzzy sets and genetic algorithm (GA). The program improved the flexibility of process plans, and provided optional process plan for job-shop scheduling.
Next, aims to job-shop scheduling problem, a process time pace network model has been constructed under multi-process plans, it provided a particular idea for modeling the job-shop scheduling. For the lopsided load of machines, load balancing model of process routes is established based on Wardrom User Equilibrium (UE) principle, and a improved genetic algorithm is designed based on UE for solving the JSP with non-linear process time and multi-process plans, and the effectiveness of the algorithm designed has been validated by comparing with other algorithms and other commercial software.
At last, according to a spaceflight manufacturing enterprise, and select a process task with non-linear process time and multi-process rotues as case study, by applying the achievement of this research, the effectiveness of this algorithm designed has been validated by comparing with other algorithms and other commercial software. Finally, a softeware tools of manufacturing executive system (MES) has been inrodued simply.
引文
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