Neighborhood Search for Process Resource Configuration in Cyber Physical Systems

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.