Task scheduling strategy for 3DPCP considering multidynamic information perturbation in green scene

• Main Authors: HE, JianJia, WU, Jian, SIAU, Keng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Green Scene; Multidynamic Information; 3D Printing Cloud Platform (3DPCP); Task Scheduling; Heuristic Scheduling Strategy; Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/9343; https://ink.library.smu.edu.sg/context/sis_research/article/10343/viewcontent/Task_Scheduling_Strategy_for_3DPCP_Considering_Mul.pdf
• Institution: Singapore Management University

The 3D printing cloud platform (3DPCP) plays a pivotal role in breaking down the information silos between supply and demand, effectively reducing waste through information integration and intelligent production. However, due to the complexity of 3DPCP scheduling in green scenes and the multidynamic information perturbations, unveils problems in traditional task scheduling methods in 3DPCP. These issues manifest as incomplete considerations, subpar green performance, and weak adaptability to dynamic changes. There is an urgent need to design practical methods to realize the multidynamic information perturbations in green scenes within 3DPCP. Therefore, this article first defines the 3DPCP task scheduling problem for multidynamic information perturbation in green scenes. Second, the article proposes a task scheduling model and a heuristic task scheduling strategy to minimize both the average cost and carbon dioxide (CO2) emissions per unit of quality product. Finally, the article validates effectiveness and superiority of the proposed strategy through simulation experiments.