【论文信息】

Yang T, Jiang F, & Su JF*. (通讯作者). A service composition optimization approach for cloud manufacturing based on the dual-layer coupled network and IPSO algorithm[J].Computers & Industrial Engineering（中科院SCI二区TOP期刊）. 2025,210:111529. https://doi.org/10.1016/j.cie.2025.111529.

【作者信息】

第一作者：杨涛，博士、副教授、硕士生导师，研究方向：客户协同创新管理、商业模式创新、工业工程与管理；

第二作者：蒋芳，2023级企业管理硕士研究生，研究方向：智能制造与网络协同制造；

通讯作者：苏加福，博士、教授、研究生导师，研究方向：多属性决策理论与方法、协同创新复杂系统管、创新网络知识管理。

【基金支持】

国家自然科学青年基金（71701027）、重庆市教委人文社会科学研究项目（25SKGH117）和重庆市研究生科研创新项目（CYS240543）。

【论文摘要】

In the complex and dynamic domain of cloud manufacturing (CMfg), effective service integration—balancing cost minimization, quality optimization, and efficiency maximization—is crucial for platform stability and business scalability. The heterogeneous and uncertain nature of manufacturing resources, coupled with intricate interactions among CMfg entities, presents significant challenges to optimizing service composition. This paper proposes a novel optimization approach that integrates a dual-layer coupled network model with an improved particle swarm optimization (IPSO) algorithm. First, a dual-layer coupled network is constructed to model the relationships between service providers and service demanders. Second, based on topology analysis, a weighted sum of node centrality metrics in the provider layer is utilized for initial screening. Third, a multi-objective optimization model is formulated and solved using the IPSO algorithm. IPSO enhancement entails dynamic adjustment of the inertia weight and learning factors, thereby improving the global search performance and local optimization accuracy. The effectiveness, robustness, and superiority of the proposed algorithm are demonstrated through a comprehensive case study, sensitivity analysis, and comparative evaluation against benchmark algorithms.