Neighborhood Search for Process Resource Configuration in Cyber Physical Systems

Fu-Shiung Hsieh
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Abstract

Cyber-Physical Production Systems (CPPS) consists of intertwined physical components and software components that interact with each other to accommodate changes and demands in the business world. Software components in CPPS must generate the information or instructions to guide the operations of physical components based on the real-time states acquired by sensors from the shop floor. In this paper, we will focus on process optimization issue for the development of software components in CPPS. This paper aims to propose a more efficient solution algorithm to find a solution. In this paper, we will enhance the search capabilities of discrete Differential Evolution approach by a neighborhood search method. Neighborhood search explores the neighborhood of the current solution to find a potential better solution that can improve the current solution. By adopting the concept of neighborhood search, we will propose a more effective discrete Differential Evolution approach through combining the neighborhood search with existing search strategies of Differential Evolution. To verify performance and efficiency of the algorithm, we create several test cases to perform experiments to compare with previous algorithms based on experimental results. We illustrate efficiency of the proposed method by analyzing the results.
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网络物理系统中进程资源配置的邻域搜索
信息物理生产系统(CPPS)由相互交织的物理组件和软件组件组成,它们相互作用以适应商业世界中的变化和需求。CPPS中的软件组件必须根据传感器从车间获取的实时状态生成指导物理组件操作的信息或指令。在本文中,我们将重点讨论CPPS中软件组件开发的过程优化问题。本文旨在提出一种更有效的求解算法来寻找解。在本文中,我们将通过邻域搜索方法来增强离散差分进化方法的搜索能力。邻域搜索探索当前解的邻域,以找到一个可能更好的、可以改进当前解的解。采用邻域搜索的概念,将邻域搜索与现有的差分进化搜索策略相结合,提出一种更有效的离散差分进化方法。为了验证算法的性能和效率,我们创建了几个测试用例进行实验,并根据实验结果与以前的算法进行比较。通过对结果的分析,说明了所提方法的有效性。
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