基于和声搜索算法的云制造服务组合优化研究

ABSTRACT

Cloud manufacturing is a new kind of manufacturing model which is service-oriented,networked and intelligent.It mergers some technologies together such as cloud computing,big data,Internet of Things and high performance computing technology and carries through virtualization encapsulation on manufacturing resources and manufacturing capacity,so as to form cloud manufacturing services and make them merger together to form a resource pool of cloud manufacturing services.The cloud manufacturing system combines and calls cloud manufacturing services resources according to the needs which are submitted by users in the cloud manufacturing platform.Therefore,manufacturing services resources can be responded and scheduled more efficiently and can also be configured in a more reasonable way.However,in the process,how to better realize the optimization of cloud manufacturing services combination is the key problem that needs to be further researched.

The cloud manufacturing model reorganizes the loosely distributed manufacturing service resources and builds a manufacturing resource pool that is managed and scheduled by the cloud manufacturing platform by integrating large-scale,diversified,discrete manufacturing resources and capabilities.The cloud manufacturing service portfolio is an orderly combination of cloud services according to certain rules. Each tightly-coordinated manufacturing service chain is formed for manufacturing tasks.The appropriate method is used to optimize the composite service so that the combined manufacturing cloud service meets customer satisfaction in terms of manufacturing time,cost,and quality,etc.Among them,the process of portfolio service optimization has become an NP-hard problem due to the large number of selectable manufacturing services and manufacturing service portfolio paths.

The optimization problem of cloud manufacturing services combination is a typical NP-hard problem, which is nonlinear,multiple-targeted and uncertain that makes the problem face many challenges when the model is established.This paper modifies the time calculation method of the model in the existing literature, first discriminates the service with the largest service execution time in the parallel service,and then counts it into the total service execution time.The modified model was solved by the harmony search algorithm and the results of different parameters were compared and analyzed.The results show that the combination

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of the cloud manufacturing service sequence obtained by adding the user's expected model can reach a higher level.The user expects the degree of completion.At the same time,the solution process shows that the harmony search algorithm has great potential for solving cloud manufacturing service composition optimization problems.Finally,this paper analyzes the same type of multi-task service composition process in cloud manufacturing,and constructs the same multi-task service optimization model of cloud manufacturing that considers the average degree of completion of multi-task users,and uses the harmony search algorithm to solve the examples.At the same time,the combination of cloud manufacturing service sequences that allows users of multiple tasks to expect a high degree of completion indicates that the model built can reflect the expectations of multiple users to a certain extent,so that the resulting service sequence combination is closer to the user's needs.It has enriched the relevant research on cloud manufacturing multi-task service composition optimization issues and has certain reference value for further research in the future.

KEY WORDS:Cloud manufacturing,cloud manufacturing service combination,service combination optimization,harmony search algorithm

摘要.........................................................................................................................................I ABSTRACT.............................................................................................................................III 1绪论.. (1)

1.1研究背景及意义 (1)

1.1.1研究背景 (1)

1.1.2研究意义 (2)

1.2国内外研究现状 (3)

1.2.1云制造 (3)

1.2.2云制造服务组合 (4)

1.2.3云制造多任务服务组合 (5)

1.2.4云制造服务组合优化 (6)

1.2.5和声搜索算法 (9)

1.3本文的创新点 (10)

1.4论文结构安排 (11)

2相关理论基础 (13)

2.1云制造服务组合 (13)

2.1.1云制造及云制造服务 (13)

2.1.2云制造服务组合 (14)

2.1.3云制造服务组合的特点 (15)

2.2和声搜索算法 (16)

2.2.1算法原理 (16)

2.2.2算法运算流程 (17)

2.2.3算法参数讨论 (20)

2.2.4算法的特征 (20)

3和声搜索算法求解云制造单任务服务组合优化问题 (23)

3.1云制造服务组合优化问题特征分析 (23)

3.2云制造单任务服务组合执行路径与服务时间分析 (24)

3.3云制造单任务服务组合优化模型 (25)

3.3.1问题描述 (25)

3.3.2模型描述 (26)

3.3.3模型讨论 (28)

3.4云制造单任务服务组合求解结果评价 (28)

3.4.1云制造单任务服务组合算例描述 (28)

3.4.2云制造单任务服务组合优化模型求解 (29)

3.4.3云制造单任务服务组合对比模型求解与比较 (35)

4和声搜索算法求解云制造多任务服务组合优化问题 (39)

4.1云制造同类型多任务服务组合流程 (39)

4.2云制造同类型多任务服务组合优化模型 (40)

4.2.1问题描述 (40)

4.2.2模型建立 (41)

4.2.3模型讨论 (43)

4.3云制造同类型多任务服务组合优化模型求解 (43)

4.3.1算例求解 (43)

4.3.2求解结果分析 (46)

5结论与展望 (47)

5.1研究结论 (47)

5.2研究展望 (48)

参考文献 (49)

致谢 (55)

摘要

1绪论

1.1研究背景及意义

1.1.1研究背景

制造业在我国国民经济体系中占据重要地位，但是，随着世界经济格局逐渐变化，中国制造业凭借廉价劳动力打开世界市场的优势已不明显，迫切需要转型升级，发展现代制造业，实现生产型制造向服务型制造的转变，以制造即服务的理念促进制造业自主创新和结构调整。然而，当前我国的自主创新能力不足、制造业生产模式落后、制造资源的分布和应用存在巨大的不均衡，资源利用率低，环境污染严重。一些企业大量的制造资源和制造能力处于闲置状态而不能得到有效共享，综合效能无法得以发挥；而另一些企业在面对用户需求时却存在着产品和服务供不应求的状况，往往因缺乏相应的软、硬制造资源来对产品进行设计和研制而错失市场良机。

另外，各企业基于自身发展考虑而选择的软硬件资源运行在不同的平台和系统之中，造成跨企业的资源难以集成并共享。如何在生产制造过程中充分利用闲置资源和整合社会化存量资源，提高资源利用率，减少资金投入，降低能源消耗和污染程度以实现高效、优质、低耗的绿色制造和低碳制造，加快转变经济发展方式以逐步实现生产加服务型制造和中国创造，仍然是我国制造业急需解决的关键性问题，而要解决这些问题，迫切需要探索、培育并发展新型的制造业信息化模式与技术手段[1]。

因此，“中国制造2025”战略被提出，该战略的主攻方向是智能制造，智能制造已经成为了该战略的重点研究领域，物联网、云计算、高性能计算等信息技术的发展及应用，必将对制造业转型升级产生巨大的推动作用，云制造的概念正是在这样的背景下被提出的，是一种面向服务的、融合物联网、云计算、高性能计算等技术的网络化制造新模式[2]。

云制造模式利用先进的互联网技术使得制造过程中存在的地理限制被打破，通过虚拟化技术将分布异构的制造资源转化为云服务存储于云制造系统资源池中，实现制造资源的集成统一管理，用户只要通过互联网就能向云制造系统提出产品设计、制造、包装等制造全生命周期的各类服务请求，方便地获取需求的制造服务。云制造模式将松散分