关键词: 产品线, 云制造, 设计, 非线性双层规划, 嵌套Levy-Jaya算法

Abstract: Due to the penetration of new generation advanced information technologies such as cloud computing, big data, and the Internet of Things in the manufacturing field, the close integration of manufacturing and information technology has become an inevitable trend for future development. The cloud manufacturing model has also become a hot research topic in today’s academic community. As a core strategy for companies to meet the diverse needs of customers, product lines have had a broad and profound impact on industry since its concept was first introduced. This impact is not only reflected in the fact that a diversified product range within a product line allows companies to cover a broader market demand, reduce the risks associated with dependency on a single product, satisfy the varying preferences of different consumers, and increase market share, but also in the shift from centralized to decentralized production methods, which has fostered the development of related industries such as logistics. In the academic world, product lines have also gained increasing attention in recent years. These theoretical studies encompass various aspects, including design, manufacturing, logistics, and marketing, with product line design, as the core link in the entire value chain process, becoming a central focus of researchers. However, existing researches on product line design mainly focus on the performance of product varieties in the market, and there is little research literature that delves into the inherent interactive influence relationship between architecture design and engineering manufacturing within product lines. Thus, this paper emphasizes the inherent interactive influence relationship between product line design and cloud manufacturing decisions, and proposes a hierarchical joint optimization approach.
A nonlinear bi-level programming model is formulated to reveal the complex interaction process between product line design and cloud manufacturing decisions. The manufacturer in the upper-level model designs the product line architecture to maximize its expected profit. In the lower-level model, multiple service providers on the cloud manufacturing service platform simultaneously optimize the types of cloud manufacturing product modules to maximize their respective expected profits, and the decisions among them are mutually independent. A nested Levy-Jaya algorithm is developed to solve the model. A cloud manufacturing case study of electric vehicle product line is presented to demonstrate the feasibilities of the model and algorithm.
Our research findings have several important managerial implications: (1)There is a leader-follower joint influence between product line design and cloud manufacturing decisions. Thus, the optimization approach for them should also be a hierarchical optimization. (2)The proposed non-linear bi-level programming model exemplifies a typical hierarchical interactive optimization problem, which is easy to expand and apply. Therefore, it has universal research significance and practical value. (3)The nested Levy-Jaya algorithm has superior performance and stability in solving bi-level programming models.
Compared with previous researches, the major contributions of this study are as follows. (1)By establishing an interactive decision mechanism between product line design and cloud manufacturing decisions, the leader-follower interactive influence and complex decision-making process between them are analyzed in detail. (2)We establish a game-theoretic model based on Stackelberg game theory to quantitatively optimize the complex decision process of product line design and cloud manufacturing decisions, and address technical difficulties in constructing its mathematical expressions. (3)Aimed at the complexity of solving the non-linear bi-level programming model proposed in this paper, an improved nested Levy-Jaya algorithm is developed to solve the model by combining the global search strategy of Levy distribution random walk and the efficient search efficiency of Jaya algorithm.

Key words: product line, cloud manufacturing, design, nonlinear bi-level programming, nested Levy-Jaya algorithm