云制造环境下柔性作业车间调度算法的研究

发布时间：2018-05-15 06:03

本文选题：云制造 + 柔性作业车间　；参考：《哈尔滨理工大学》2017年硕士论文

【摘要】：我国是制造资源大国,但是制造资源的利用率不高,浪费的情况很严重。云制造的兴起,为制造业带来了新的机遇,因为它体现了将分散在各地的资源进行集中使用和将集中在一起的资源进行分散去提供服务的思想,以多对多的服务思想,将分布式资源进行集中的管理,使得制造资源的共享和利用能够达到最大程度的实现,企业的生产效益能够实现最大化,同时为客户满足需求,生产高质量的产品,为了达到这一目标,本文主要研究云制造资源优化调度和企业车间制造资源调度问题。首先,本文综述了云制造理论、云制造优化配置方法、云制造环境下的柔性作业车间调度的国内外相关领域的研究现状,阐明了目前研究所存在的不足。之后对云制造环境下的制造资源进行分类并阐述了其特征,对云制造环境下的资源虚拟化进行了研究,提出了虚拟化框架,并对虚拟化的资源信息进行形式化的描述,来满足请求端提出的制造设备资源需求。其次,本文先从云平台角度出发,对云平台调度进行了资源匹配,建立了调度数学模型,给出目标函数和约束条件,提出了改进的蚁群算法来解决云制造的优化调度问题,用实例和其他算法进行比较来验证蚁群算法的实用性和高效性。最后,从企业制造车间角度提出了在云制造环境下的柔性作业车间调度产生的新问题,即在加入了云制造这一元素后,传统的车间调度任务发生了改变,使得原来的设备能力变成了离散型设备能力区间。针对这一问题,提出了启发式-蚁群算法,采用分层的方法,用蚁群算法对工序进行选择,用启发式规则对机器进行选择。最后用实例和其他算法比较来验证本文算法的优越性。
[Abstract]:China is a large country of manufacturing resources, but the utilization rate of manufacturing resources is not high, and the situation of waste is very serious. The rise of cloud manufacturing has brought new opportunities for manufacturing, because it embodies the idea of centralizing the resources scattered around the world and decentralizing the resources concentrated together to provide services, with a many-to-many service idea. Centralized management of distributed resources enables the sharing and utilization of manufacturing resources to achieve maximum realization, the production efficiency of enterprises can be maximized, at the same time to meet the needs of customers and produce high-quality products, In order to achieve this goal, this paper mainly studies the optimal scheduling of cloud manufacturing resources and the scheduling of enterprise workshop manufacturing resources. Firstly, this paper summarizes the research status of cloud manufacturing theory, cloud manufacturing optimization configuration method, flexible job shop scheduling in cloud manufacturing environment at home and abroad, and clarifies the shortcomings of the present research. Then the manufacturing resources in the cloud manufacturing environment are classified and their characteristics are expounded. The virtualization of resources in the cloud manufacturing environment is studied, and the virtualization framework is proposed, and the resource information of the virtualization is described formally. To meet the resource requirements of the manufacturing equipment proposed by the requester. Secondly, from the point of view of cloud platform, this paper makes resource matching for cloud platform scheduling, establishes scheduling mathematical model, gives objective function and constraint conditions, and proposes an improved ant colony algorithm to solve the optimal scheduling problem of cloud manufacturing. The practicability and efficiency of ant colony algorithm are verified by comparing with other algorithms. Finally, a new problem of flexible job shop scheduling in the cloud manufacturing environment is put forward from the point of view of enterprise manufacturing shop. That is, after adding the element of cloud manufacturing, the traditional job shop scheduling task has changed. Make the original equipment capacity into discrete equipment capacity range. In order to solve this problem, a heuristic ant colony algorithm is proposed. The hierarchical method is used to select the process and the heuristic rule is used to select the machine. Finally, the superiority of this algorithm is verified by comparing it with other algorithms.
【学位授予单位】：哈尔滨理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TB497;TP18

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