网络化制造资源优化配置研究
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摘要
随着信息技术、网络技术、特别是Internet技术的迅速发展和广泛应用，网络化制造成为近年来最具潜力的制造模式。实现网络化制造的核心及其重要目标就在于制造资源的优化配置，网络化制造资源优化配置的研究不仅可以丰富和发展先进制造模式及网络化制造的相关理论和方法，促进相关学科的发展，而且从实际应用角度看，通过实施网络化制造资源优化配置，可以在全社会范围内实现制造资源的优化整合，提高制造资源的利用率、提高我国制造业的整体效益。
本文针对网络化制造环境下的制造资源优化配置问题，从总体设计、数学建模、核心算法设计、以及系统实现等方面进行了深入的研究，主要的研究内容和成果如下：
(1) 网络化制造资源优化配置的两级优化策略
提出了网络化制造资源优化配置的两级优化策略：即物理制造单元优选、工艺规程调度仿真优化；提出了两阶段的物理制造单元优选：即物理制造单元类型选择、可执行加工路线优化。
(2) 物理制造单元类型选择
建立了基于成组技术的制造特征分类编码系统，讨论了物理制造单元类型选择的基本步骤，研究了基于BP神经网络的物理制造单元制造能力评价，并针对神经网络的收敛速度慢及易陷入局部极小等缺点，提出了一种混合遗传算法来优化神经网络的结构并确定网络各层之间的连接权值与阈值，通过实例仿真验证了算法的有效性。
(3) 可执行加工路线优化
首先建立了可执行加工路线优化的数学模型，确定了模型的决镣空间、目标函数、及约束条件，并指出该模型属于复杂的多目标、多选择、多约束背包问题；然后分析了多目标多选择多约束背包问题及多目标优化问题的研究现状；在此基础之上，将可执行加工路线优化模型分成两种情况进行处理：当决策者明确给出时间、成本、可靠性三方面的目标权重信息时，将问题转化为单目标优化问题并提出了一种多选择多约束遗传算法求得最优解；当无法获得权重时提出了一种并行多目标妥协遗传算法进行求解，算法采用基于排列的编码方式，由多个子种群独立进化并定期交换最佳个体，适应度计算采用自适应权重方法及基于距离度量的妥协方法，并通过适应度共享保持种
With the rapid development and wide use of information technology, network technology, and the Internet technology, networked manufacturing has become the most promising manufacturing mode in recent years. One of the cores and important objectives of networked manufacturing is the optimizing configuration of manufacturing resources. The research on Networked Manufacturing Resources Optimizing Configuration (NMROC) not only can enrich and develop the relevant theories and methods of advanced manufacturing mode and networked manufacturing, so to promote the development of pertinent subjects, and by implementing NMROC, as seen from the viewpoint of practicality, but also can realize the optimizing rearrangement of manufacturing resources in the whole society, so to enhance the efficiency of manufacturing resources and the whole benefit of manufacturing industry in our country.
The dissertation deals with the optimizing configuration of manufacturing resources in the networked manufacturing environment. The research discusses in detail about the overall designing, mathematical modeling, key algorithms designing, and system realization. The main contents and achievements of the dissertation are as follows:
(1) Two Levels Optimizing Strategy of NMROC
The two levels optimizing strategy of NMROC is proposed, namely the optimization of Physical Manufacturing Unit (PMU), and the simulating optimization of process and schedule. And the two phases optimization of PMU is brought forward, namely the selection of PMU's type, and the optimization of Executable Manufacturing Process (EMP).
(2) Selection of PMU's Type
The classifying and coding system of manufacturing characteristics basing on group technology is established. And the procedure of the selection of PMU's
本文针对网络化制造环境下的制造资源优化配置问题，从总体设计、数学建模、核心算法设计、以及系统实现等方面进行了深入的研究，主要的研究内容和成果如下：
(1) 网络化制造资源优化配置的两级优化策略
提出了网络化制造资源优化配置的两级优化策略：即物理制造单元优选、工艺规程调度仿真优化；提出了两阶段的物理制造单元优选：即物理制造单元类型选择、可执行加工路线优化。
(2) 物理制造单元类型选择
建立了基于成组技术的制造特征分类编码系统，讨论了物理制造单元类型选择的基本步骤，研究了基于BP神经网络的物理制造单元制造能力评价，并针对神经网络的收敛速度慢及易陷入局部极小等缺点，提出了一种混合遗传算法来优化神经网络的结构并确定网络各层之间的连接权值与阈值，通过实例仿真验证了算法的有效性。
(3) 可执行加工路线优化
首先建立了可执行加工路线优化的数学模型，确定了模型的决镣空间、目标函数、及约束条件，并指出该模型属于复杂的多目标、多选择、多约束背包问题；然后分析了多目标多选择多约束背包问题及多目标优化问题的研究现状；在此基础之上，将可执行加工路线优化模型分成两种情况进行处理：当决策者明确给出时间、成本、可靠性三方面的目标权重信息时，将问题转化为单目标优化问题并提出了一种多选择多约束遗传算法求得最优解；当无法获得权重时提出了一种并行多目标妥协遗传算法进行求解，算法采用基于排列的编码方式，由多个子种群独立进化并定期交换最佳个体，适应度计算采用自适应权重方法及基于距离度量的妥协方法，并通过适应度共享保持种
With the rapid development and wide use of information technology, network technology, and the Internet technology, networked manufacturing has become the most promising manufacturing mode in recent years. One of the cores and important objectives of networked manufacturing is the optimizing configuration of manufacturing resources. The research on Networked Manufacturing Resources Optimizing Configuration (NMROC) not only can enrich and develop the relevant theories and methods of advanced manufacturing mode and networked manufacturing, so to promote the development of pertinent subjects, and by implementing NMROC, as seen from the viewpoint of practicality, but also can realize the optimizing rearrangement of manufacturing resources in the whole society, so to enhance the efficiency of manufacturing resources and the whole benefit of manufacturing industry in our country.
The dissertation deals with the optimizing configuration of manufacturing resources in the networked manufacturing environment. The research discusses in detail about the overall designing, mathematical modeling, key algorithms designing, and system realization. The main contents and achievements of the dissertation are as follows:
(1) Two Levels Optimizing Strategy of NMROC
The two levels optimizing strategy of NMROC is proposed, namely the optimization of Physical Manufacturing Unit (PMU), and the simulating optimization of process and schedule. And the two phases optimization of PMU is brought forward, namely the selection of PMU's type, and the optimization of Executable Manufacturing Process (EMP).
(2) Selection of PMU's Type
The classifying and coding system of manufacturing characteristics basing on group technology is established. And the procedure of the selection of PMU's
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