具有多模式的FFS作业计划制定方法

发布时间：2018-01-07 22:23

本文关键词：具有多模式的FFS作业计划制定方法　出处：《广东工业大学》2012年硕士论文　论文类型：学位论文

【摘要】：柔性流水作业车间调度问题是传统车间作业调度问题的扩展,该类调度更加灵活,也更加符合实际车间生产情况,是迫切需要解决的一类调度问题。目前很多针对柔性流水作业车间调度问题的研究均将问题建立在工件不存在资源多模式的基础上,而在实际生产过程中,工件在加工过程中往往具有多种加工模式可选,一种加工模式代表一组资源需求量及相应任务工期,不同的资源投入量对应不同的任务工期。在任务具有多种执行模式的情况下,合理安排任务的执行模式可以节约资源、降低成本、缩短工期。因此,研究多模式下柔性流水车间调度问题就显得十分有意义。本文首先采用数学规划的方法对多模式下柔性流水车间调度问题进行建模,建立了基于JIT生产模式的目标函数,并考虑了加工模式的设备资源约束。其次,针对问题的特点,设计了一种混合蚁群算法求解上述调度模型。该算法第一部分利用蚁群算法确定部件的加工工作中心和加工模式,第二部分利用部件优先级来确定工作中心前的部件任务队列顺序。然后,将蚁群算法应用在实际问题中。第一步,利用蚁群算法求解柔性流水车间调度问题中的三个基准实例,并将求解结果与其他算法求解结果对比,以此说明蚁群算法在解决该类问题的有效性和优越性。第二步,通过企业实际生产数据构建了仿真实例,利用混合蚁群算法对五组数据分别进行了求解,并将求解结果与其他文献中的蚁群算法求解结果对比,以此说明本文对蚁群算法中信息素更新规则的改进十分有效。第三步,考虑到生产车间的实际情况,应用蚁群算法设计了一种基于滑动窗口机制的滚动调度策略,并用测试实例说明了策略的有效性。最后,以合作企业的车间为背景,在现有ERP系统的基础上,构建了以蚁群算法模块为核心的部件调度系统框架,并且.详细说明了系统总体流程。
[Abstract]:Flexible flow shop scheduling problem is an extension of the traditional job shop scheduling problem. This kind of scheduling is more flexible and more in line with the actual production situation. It is an urgent need to solve a kind of scheduling problem. At present, many researches on flexible flow shop scheduling problem are based on the fact that there is no resource multi-mode in the workpiece, but in the actual production process. In the process of workpiece processing, there are many kinds of machining modes that can be selected, one kind of processing mode represents a group of resource demand and the corresponding task duration. Different resource inputs correspond to different task duration. When the task has multiple execution modes, reasonably arranging the task execution mode can save resources, reduce cost and shorten the duration. It is very meaningful to study the flexible income job shop scheduling problem in multiple modes. In this paper, the mathematical programming method is used to model the flexible income job shop scheduling problem in multiple modes, and the objective function based on JIT production mode is established, and the equipment resource constraints in the machining mode are considered. Secondly, according to the characteristics of the problem, a hybrid ant colony algorithm is designed to solve the above scheduling model. The first part of the algorithm uses ant colony algorithm to determine the machining center and processing mode of components. The second part uses component priority to determine the order of component task queue before work center. Then, the ant colony algorithm is applied to the practical problem. The first step is to use the ant colony algorithm to solve the flexible income job shop scheduling problem with three benchmark examples, and the results are compared with the results of other algorithms. In order to illustrate the effectiveness and superiority of ant colony algorithm in solving this kind of problem. The second step, through the actual production data of the enterprise to build a simulation example, using the hybrid ant colony algorithm to solve the five groups of data respectively. The results are compared with the results of ant colony algorithm in other literatures, which shows that this paper is very effective to improve the pheromone updating rules in ant colony algorithm. The third step, considering the actual situation of the production workshop. A rolling scheduling strategy based on sliding window mechanism is designed by using ant colony algorithm, and the effectiveness of the strategy is illustrated by a test example. Finally, based on the existing ERP system, a component scheduling system framework with ant colony algorithm module as the core is constructed based on the workshop of the cooperative enterprise, and the overall flow of the system is explained in detail.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH165

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