Multi-service collaboration and composition of cloud manufacturing customized production based on problem decomposition
원문 초록
Cloud manufacturing system is a service-oriented and knowledge-based one, which can provide solutions for the large-scale customized production. The service resource allocation is the primary factor that restricts the production time and cost in the cloud manufacturing customized production (CMCP). In order to improve the efficiency and reduce the cost in CMCP, we propose a new framework which considers the collaboration among services with the same functionality. A mathematical evaluation formulation for the service composition and service usage scheme is constructed with the following critical indexes: completion time, cost, and number of selected services. Subsequently, a problem decomposition based genetic algorithm is designed to obtain the optimal service compositions with service usage schemes. A smart clothing customization case is illustrated so as to show the effectiveness and efficiency of the method proposed in this paper. Finally, the results of simulation experiments and comparisons show that these solutions obtained by our method are with the minimum time, a lower cost, and the fewer selected services.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
RLHGNN: Reinforcement Learning-driven Heterogeneous Graph Neural Network for Next Activity Prediction in Business Processes
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
RAISE: Enhancing Scientific Reasoning in LLMs via Step-by-Step Retrieval
TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via Large Language Models
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
SparseLLM: Towards Global Pruning for Pre-trained Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.